First DNA Barcode Reference Library for the Identification of South American Freshwater Fish from the Lower Paraná River

Valid fish species identification is essential for biodiversity conservation and fisheries management. Here, we provide a sequence reference library based on mitochondrial cytochrome c oxidase subunit I for a valid identification of 79 freshwater fish species from the Lower Paraná River. Neighbour-joining analysis based on K2P genetic distances formed non-overlapping clusters for almost all species with a ≥99% bootstrap support each. Identification was successful for 97.8% of species as the minimum genetic distance to the nearest neighbour exceeded the maximum intraspecific distance in all these cases. A barcoding gap of 2.5% was apparent for the whole data set with the exception of four cases. Within-species distances ranged from 0.00% to 7.59%, while interspecific distances varied between 4.06% and 19.98%, without considering Odontesthes species with a minimum genetic distance of 0%. Sequence library validation was performed by applying BOLDs BIN analysis tool, Poisson Tree Processes model and Automatic Barcode Gap Discovery, along with a reliable taxonomic assignment by experts. Exhaustive revision of vouchers was performed when a conflicting assignment was detected after sequence analysis and BIN discordance evaluation. Thus, the sequence library presented here can be confidently used as a benchmark for identification of half of the fish species recorded for the Lower Paraná River.


Introduction
Reliable species identification is necessary for conservation and sustainable exploitation of natural resources. DNA sequences of highly conserved genes have been used as a tool to identify biological species. This approach became especially relevant when identification based on morphological characters is not possible (e.g. larvae, eggs and fragmented tissue). A short Given the great power of DNA barcoding to identify fish species and considering the unique assemblage of Lower Paraná River fish along with future changing scenarios, the present study aimed to group the first comprehensive reference COI sequence library for fishes of this region. Also, to test the effectiveness of the barcoding methodology for their identification in future studies.

Specimen collection and sampling area
Several fishing techniques were used for sampling. Sampling methods included gill nets, lift nets, slat traps, hoop nets and angling. Animals were handled with maximum care to prevent or minimize injuries during studies. All sampling procedures and methods were in accordance with the FishBol international project recommendations and the Guidelines for the use of fishes in research by the American Fisheries Society.
A total of 308 specimens were sampled between 2012 and 2013 from a wide area of the Lower Paraná River near the city of Rosario (50 sampling points, site 1) with the exception of 8 specimens obtained at one sampling point at site 2 (Fig 1). The locations involved in the study were not part of any protected area, reserve forests or national parks. The General Direction of Natural Resources of the Production Ministry from Entre Rios Province in compliance with the law N°4892/70, issued the permission to conduct this study in Paraná River and Delta from Diamante to Gualeguay city. No specific permissions were required for sampling point 2 since tissue samples and photograph of Specimens were obtained from sport and commercial fishermen. The selected area encompasses a variety of environments, such as lagoons, streams, wetlands, the main river channel and its coasts. Collected specimens were anesthetized by immersion in 1% benzocaine in water and euthanized by benzocaine excess. A small piece (5-7 mm³) of muscle or fin tissue was removed from the right side of each fresh fish and preserved in 96% ethanol at -20°C. Specimens were photographed, labeled and fixed in 10% formaldehyde solution for 7 days. Occasionally, tissues were collected through the support of fisherman. Tissues and vouchers specimens were stored in 96% ethanol and deposited in the Fish Collection of the Angel Gallardo Natural Sciences Provincial Museum, Rosario, Argentina. Some tissue samples lack morphological vouchers, but have a "photographic voucher" according to the Fish-BOL collaborator's protocol [28]. All specimens for this study were obtained in compliance with animal welfare laws, local guidelines and national policy in the realm of the Argentine Republic.

Sequence alignment and data analysis
Bidirectional sequences were assembled in SEQSCAPE version 2.1.1 (Applied Biosystems, Foster City, CA, USA), and manually edited. Assembled DNA sequences were submitted to Gen-Bank (accession numbers: KU288760-KU289067).
The COI assemble sequences were analyzed using Alignment Browser and Sequence Composition tools, both available in the Sequence Analysis Module of BOLD. Genetic distances among and within species were estimated using MEGA, version 6.0 [52]. The applied model of nucleotide substitution was estimated using the best fit substitution model tool [53] available in the same software. General time reversible substitution model (GTR) with a Gamma distribution of variable sites and invariable sites was the model that best fit the substitution pattern of the dataset with ti/tv = 3.48, α = 0.83, and I = 0.56.
Genetic distances among and within species were also estimated using the Kimura two-parameter (K2P) substitution model [54], implemented in the Distance Summary tool in BOLD. This is the standard model for DNA barcoding data sets and one of the most commonly used models to describe distance between species using COI. Since no significant differences were found in estimated distances and tree topologies between GTR and K2P models, the latter was chosen for comparison purposes. Haplotype identification was performed using DnaSP 5.10.01 [55].
Neighbour Joining (NJ) and Maximum Likelihood (ML) trees based on K2P genetic distance were created to provide a graphic representation for the patterning of distance between species using the MEGA 6 software [52]. Node robustness was inferred with 1000 bootstrap replicates. Comparisons at the species level of the maximum intraspecific genetic distance with the minimum distance to the nearest neighbour were performed applying the BOLD's 'Barcoding Gap Analysis' tool.
Three different clustering methods, Barcode Index Number (BIN) system [5], Poisson Tree Processes (PTP) model [6] and Automatic Barcode Gap Discovery (ABGD) [7], were used to confirm the concordance between sequence clusters and species designations by taxonomy. These methods were selected based on their general popularity and strong performance in previous studies [56,57]. The three methods clustered COI sequence data into operational taxonomic units (OTUs) independent of prior taxonomic assignment. PTP reports were generated with default settings using the ML solution. ABGD clustering was carried out using the K2P distance model applying the following parameters: Pmin = 0.001, Pmax = 0.1; Steps 20; Nb bins = 20. We implemented a range of values for the gap width (X), between 0.1 and 1.5 to assess the consistency of inferred groups under varying gap width values.
Sequence comparisons with previously known sequences and close species were performed by BLAST (Basic Local Alignment Search Tool; http://www.ncbi.nlm.nih.gov/BLAST) and the BOLD Identification System (IDS) (www.boldsystems.org).
Diagnostic characters among sets of sequences were examined using BOLD's Diagnostic Character analysis tool. Concordance between BINs assignment and species identification by classical taxonomy was analyzed by the 'BIN Discordance Report' sequence analysis tool [5] available on BOLD. The BIN Discordance Report facilitates this check by comparing the taxonomy on selected records against all others in the BINs they are associated with. Specimens corresponding to discordant BINs were re-evaluated by a specialist in order to verify our data and correct potential misidentifications.

Results
Taxonomic identification of the 308 fish specimens resulted in 79 species (71 Genera, 35 Families and 10 Orders) from the Lower Paraná River (Fig 2; S1 Table). All collected species belong to the Class Actinopterygii with the exception of Potamotrygon motoro that belongs to the Class Chondrichthyes. Eight out of 71 genera (11.3%) were represented by more than one species (Astyanax, Characidium, Odontesthes, Pimelodus, Ageneiosus, Brycon, Crenicichla, and Cnesterodon). The number of individuals per species ranged from 1 to 10 (mean 4) with 33 species represented by more than 4 individuals and 16 species represented by one specimen.
Most species of commercial interest were represented in this study, such as the large migratory species Prochilodus lineatus, Salminus brasiliensis, Pseudoplatystoma corruscans, Brycon orbignyanus and Leporinus obtusidens. Recreational interest species such as P. motoro, Hoplias malabaricus, Odontesthes bonariensis, Gymnotus inaequilabiatus, Eigenmannia trilineata, and Hoplosternum littorale were also included. G. inaequilabiatus and E. trilineata are widely used as live bait for sport fishing [22]. Most species belong to the orders Siluriformes and Characiformes in agreement with previous reports for Neotropics [58,59]. In addition, species belonging to the orders Clupeiformes (Lysengraulis grossidens, Ramnogaster melanostoma, and Pellona flavipinnis) and Atheriniformes (O. bonariensis) that migrate from estuarine or marine environments to freshwater habitats were identified. Cyprinus carpio, an exotic species, was also reported.

DNA barcoding-specimen identification
COI amplified DNA fragments (~648 pb) were obtained from all 308 specimens. No stop codons, insertions, or deletions were found in any of the amplified sequences, suggesting that all of them constitute functional mitochondrial COI sequences. No NUMTs (nuclear DNA sequences originating from mitochondrial DNA sequences) amplifications were detected. Average nucleotide frequencies were C (27.53%), T (29.40%), A (24.82%), and G (18.04%), similar to those previously reported in other studies [60].
Relationships among sequences were represented by ML (Fig 3) and NJ (S1 Fig) trees. Both K2P ML and NJ trees grouped sequences of the same taxonomically identified species in no overlapping clusters, with the exception of two species of the genera Odontesthes (O. bonariensis and O. perugiae) which were present in the same COI cluster. Species clusters were supported with boostrap values of 100%. Deep intraspecific divergences were observed in the NJ and K2P ML analysis among some sequences of H. malabaricus, B. orbignyanus, P. motoro and Megalonema argentinum species (Fig 3).
Genetic distances increased from lower to higher taxonomic levels. The average K2P genetic distance between specimens was 0.53% within species, 12.26% within genera and 19.61% within families ( Table 1). The average K2P genetic distance within conspecific specimens was 23-fold lower than the average value found in congeneric species.
Distances between species ranged from 0.00% to 19.98% (Table 1), considering the two species of the genus Odontesthes with a very low genetic distance value ranging from 0% to 0.62% (Table 2). For the other congeneric species, minimum interspecific distances ranged from 4.06% in Pimelodus genus to 19.48% in Crenicichla genus (Table 2).
The species discrimination power of DNA barcoding was analysed by plotting the maximum intraspecific distance of each species against its minimum distance to the nearest neighbour ( Fig 5). For whole data set, with the exception of Odontesthes species sequences, genetic The K2P/ML tree of 308 COI sequences for 79 morphologically identified freshwater fish species from Lower Paraná River in Argentina. NJ tree was divided into two parts from top to bottom in order from left to right. Bootstrap values >90 for 1000 replicates are shown at each branch. The number of specimens analyzed for each species is shown between brackets. Solid triangles represent clusters of multiple specimens, with height proportional to specimen number and the horizontal width proportional to the genetic variation within each cluster. In gray are shown branches of species with high intraspecific genetic divergence and species with overlapping clusters. Columns next to the tree represent presence of recognition for each clustering method while boxes highlights the differences among methods. Specimens of Brycon orbignyanus with high genetic divergence that were re-classified as B. cf. hilarii are highlighted with "*". distances of each species to their nearest neighbours were higher than the maximum intraspecific genetic distance, showing that COI barcode could discriminate 97% of species analysed from Lower Paraná River (Fig 5).

Species delimitation
For reliable COI species assignment, all data set was analyzed by three clustering methods (BIN, ABGD and PTP) in order to confirm the concordance between sequence clusters and species designations through taxonomy.
Congruent results were obtained among the three clustering methods tested in most cases. Records were assigned to 79 BINs corresponding to 79 species identified by taxonomy experts (Fig 3). One species (Hoplosternum littorale) had no BIN, since it did not meet BOLD minimum requirements to be included in this analysis. Two species shared one same BIN (O. bonariensis and O. perugiae). New BINs for G. inaequilabiatus, P. motoro, Crenicichla vittata, Serrapinus piaba, M. argentinum, and Pachyurus bonariensis were generated. G. inaequilabiatus and P. motoro have already had records with a different BIN number. The description of new BINs for species that already had records with a different BIN number could reveal possible cryptic fish species or misidentification.
Differences between clustering methods were found in C. decemmaculatus-C. cf. raddai cluster, in which BIN and ABGD reported two groups while PTP reported only one (Fig 3).
At least two clustering methods separated three of the four taxonomic identified species with higher intraspecific divergence into two different clusters, suggesting that these three groups deserved further investigation (H. malabaricus, B. orbignyanus, and P. motoro). In the case of M. argentinum, only one cluster was defined by the three clustering methods. Little information is available about M. argentinum biology, geographical distribution and conservation status, and no molecular data has been reported until now.

Special cases
Two clusters for one taxonomic identified species. For further analyses of H. malabaricus, B. orbignyanus, and P. motoro cases, K2P-NJ trees were performed (Fig 6) using COI   and Amazonas River (AMAZ, [61]). NJ tree was rooted using an H. intermedius sequence from BSB-BOLD project. Results showed that the six sequences that grouped together in the general tree (Fig 3 and Fig 6I-a cluster A) clustered with sequences of H. malabaricus from Salado River basin (Fig 6I-b). This cluster presented a maximum divergence of 0.3% and conformed only one BIN (BOLD:AAZ3734). The sequence in a separated branch at the main tree (Fig 3  and Fig 6I-a cluster B), clustered with H. malabaricus sequences from Upper Parana River and Amazonas River basins with a maximum divergence of 0.5%, conforming another BIN (BOLD: AAB1732) (Fig 6I-b). In addition, this sequence belonged to a specimen with different phenotypic characteristics easily recognized by fishermen (H. malabaricus of "small head", Fig 6I-a,  photographs). For sampling areas covered in this work only H. malabaricus has been cited. Our results showed that deep genetic divergence for H. malabaricus also occurred in a smaller geographic scale since all individuals were sampled in the same area. Genetic and/or morphological-morphometric studies have not been reported yet for H. malabaricus from Lower Paraná River. Therefore, information obtained in this work would provide the kickoff for future research on this species complex.
The Brycon genus case. Only published sequences (n = 33) of six South American species were used: B. orbignyanus from Upper Paraná River (BOLD project code FUPR), Brycon melanopterus from Amazonas River and Brycon orthotaenia, Brycon opalinus, Brycon insignis and Brycon nattereri from Sao Francisco River (BOLD project code BSB). Comparative NJ sub-tree showed that seven COI sequences of B. orbignyanus specimens that grouped together in the general tree (Fig 3 and Fig 6II-a-cluster A) clustered with B. orbignyanus sequences from Upper Paraná River (Fig 6II-b). This group presented a mean K2P distance of 0.07% and a maximum distance of 0.16%, and belonged to the same BIN (BOLD:AAE8065). Interestingly, the other two specimens that conformed cluster B at the NJ tree in Fig 6II-a, conformed a cohesive separate cluster with a different BIN number (BOLD:AAE0479) (Fig 6II-b). In order to determine species-specific status, both sequences were compared by BLAST against the NCBI nr database and by IDS tool against BOLD database. Both sequences displayed a 99% identity with B. hilarii sequences and over 99.6% of similarity by IDS tool, showing that the vouchers might be misidentified. Only photographic vouchers were available for these two individuals, which were revised and compared with all B. orbignyanus photographic vouchers. Taking into account sequence comparison results and differences found between photographic vouchers, both BOLD records were re classified as Brycon cf. hilarii in BOLD database and in NJ tree (Fig  3). Although B. hilarii distribution corresponds to Paraguay River Basin [62], our result showed that B. hilarii could reach the Paraná River near the mouth of the Paraguay River (Fig  1, sampling site 2). However, a higher sampling effort is necessary to confirm this observation.
The P. motoro case. Two clusters were observed at the main tree with deep intraspecific divergences between them (Fig 3 and Fig 6III-a). One cluster (A) grouped three sequences (BIN BOLD:ACG6814) while the other one (B), included only one sequence (BIN BOLD: AAB5375). Comparison analysis of COI sequences was performed using sequences of three different species from Upper Paraná River (P. motoro and Potamotrygon falkneri of BOLD genetic divergence that were re-classified as B. cf. hilarii are highlighted with "*". LPR: Lower Paraná River, UPR: Upper Paraná River, AMAZ: Amazonas River, SR: Salado River and SFR: Sao Francisco River.
doi:10.1371/journal.pone.0157419.g006 Table 3. List of species with "true" discordance BINs found by the 'BIN Discordance Report' sequence analysis tool. Only BINs with species level conflicts are shown.

Identification
Conflicting project code FUPR, and Potamotrygon hystrix [63]). Comparison analysis (Fig 6III-b) revealed that the sequence at cluster B grouped with P. motoro and P. falkneri sequences from the Upper Paraná River conforming a single BIN (BOLD:AAB5375). The other three P. motoro sequences (cluster A) were displayed in a separated branch, without genetic divergence among them, and constituted a new exclusive BIN (BOLD:ACG6814). Interestingly, the three P. motoro sequences in cluster A did not cluster to any other known species of the genus with reported COI sequences. A possible explanation for this result could be the presence of a new species that share some morphological characters and pattern coloration with P. motoro, which has led to misidentification. Vouchers revision was not possible in this case since only photographic vouchers were available for these individuals.
More than one species for one cluster: Species with interspecific genetic divergence values in the same range than intraspecific genetic divergence values: O. perugiae and O. bonariensis. COI interspecific genetic K2P distance between O. perugiae and O. bonariensis was in the same range as intraspecific distances recorded for O. bonariensis. BOLD's Diagnostic Character analysis showed that there was not any exclusive nucleotide for species. Six haplotypes were observed among O. perugiae and O. bonariensis sequences, two of them were shared between specimens from both species (data not shown). Moreover, COI haplotypes were shared also with other Odontesthes species, such as O. argentinensis and O. mirinensis (Villanova GV not published results).
Barcode Index Numbers (BINs) and taxonomic concordance. To check the correlation degree between species designations by taxonomy and assigned BINs, all sequences were analyzed by the 'BIN Discordance Report' tool available within the "Sequence Analysis" module of BOLD. As a result 79 BINS were identified from 291 records that met the minimum requirements to be included in the analysis. Taxonomic concordance was found in 113 records of 27 BINs (34.2%), 1 record (Xyliphius sp.) was singleton (BINs with single specimens) (1.2%) and 177 records of 51 BINs (64.6%) were conflictive, indicating that at least two different taxonomic assignments were found in BOLD database within a single BIN.
Among the 51 discordant BINS, 6 were at the Family level (17 conflicting records), 16 at the Genus level (60 conflicting records) and 29 at the species level (100 conflicting records). After an exhaustive revision by two independent groups of fish taxonomists, who worked with identification reliability level 2 according to the Fish-BOL collaborator's protocol [28], the 17 conflicting records at the Family level as well as the 60 records at the Genus level were resolved. In most of these cases, the discordant entries were caused by misidentifications in previous BOLD data projects. Out of 29 discordant BINS at the species level, 15 were shown to exhibit 'no true' : values obtained using individuals grouped in the same BIN *: the discordance was probably caused by misidentifications **: the discordance was probably caused by COI lower species-specific power of discrimination ***: the discordance COI sequences were not published or available in public BOLD projects ****: the discordance was probably caused by a combination of tree previous cases.
doi:10.1371/journal.pone.0157419.t003 discordances, as the discordant BINS were caused by lack of taxonomic determination at species level in previous BOLD projects (S2 Table) such as species identified as sp. or cf. (e.g. Potamotrygon sp., Pimelodella cf. cristata, etc.). There were 28 conflicting taxa within the 14 "true" discordant BINS. Among these conflicting taxa common characteristics were found and records were classified in four groups in order to explain the discordance among records within a BIN (Table 3): Group I ( Ã ): the discordance was probably caused by misidentifications,; Group II ( ÃÃ ): the discordance was probably caused by COI lower species-specific power of discrimination; Group III ( ÃÃÃ ): the discordance could not be analyzed comparing involved records since COI sequences were not available in public BOLD projects. BIN discordance analysis in BOLD is performed using all record uploaded to BOLD database. However a high proportion of these records belonged to projects that are not public and sequences were not available to be used. Group IV ( ÃÃÃÃ ): the discordance was probably caused by a combination of tree previous cases. For each conflicting sequence data, the maximum intraspecific distance and nearest neighbour distance were calculated and geographic distribution of specimens and references were added when available (Table 3).

Barcoding success
The present study represents the first molecular survey of Lower Paraná River fish diversity corresponding to the Southernmost Neotropical region. Seventy nine (43%) of the 185 fish species described for the Lower Paraná River were assessed in this work using COI barcodes from a subarea of this river. The observed COI genetic distances between conspecifics and congenerics (means: 0.53% and 12.26% respectively) for Lower Paraná River fish were within the range of previously reported values from fishes of freshwater ecosystems [8,10,27,70]. All sequences of the same species formed high bootstrap-supported clusters without any overlap between species, even in species within the same genera, with the exception of Odontesthes species. Nine new records not previously studied by COI barcodes were generated and incorporated to the BOLD data system (C. cf. raddai, Schizodon platae Ã , Otocinclus arnoldi, Parastegophilus maculatus Ã , Pseudohemiodon laticeps, M. argentinum Ã , Auchenipterus nigripinnis, B. cf. hilarii and Xyliphius sp.), three of which are endemic species of Argentina ( Ã ). Our study included species that migrate from estuarine or marine environments to freshwater habitats. Reproductive activity was reported for some of them in the Lower Paraná River (e.g. L. grossidens [71]). In this regards, COI barcode reference library will contribute to future freshwater ichthyoplankton identification and life cycle monitoring.

Species delimitation and data reliability
Molecular data provide a valuable resource for preliminary species delimitations or validating traditional phenotype-based species circumscriptions [7,72]. In our study, all data set was analyzed by three clustering methods and numerous experts in order to confirm the concordance between sequence clusters and species designations by taxonomy. Analysis of the results obtained by distinct clustering methods offer an additional level of confidence in the inferred OTUs in Lower Paraná River fish. Two species (H. malabaricus and P. motoro) displayed a deep intra-specific genetic distance (>2%) and the corresponding sequences grouped into two different clusters in each one.
The genus Hoplias is distributed throughout many hydrographic systems of South America and has 11 recognized species. At least 3 of them are present in Argentina [73,74]. Only H. malabaricus was described in the Lower Parana River. H. malabaricus is considered by many authors as a complex of cryptic species that require a profound taxonomic revision [61,75]. Based on COI sequence analysis, a strong geographic structure for H. malabaricus from distant hydrographic basins in South America was previously proposed [27]. However, specimens obtained in this study from the same Paraná River area also present high COI divergence supporting the hypothesis of the existence of a cryptic species in the Lower Paraná River.
At least six freshwater stingrays species of the genera Potamotrygon are present in the Lower Parana River (P. schuhmacheri, P. hystrix, P amandae, P. brachyura, P. falknerii, and P. motoro).
Recently, a new Potamotrygon sp. was described by Almirón et al. [18], in the Paraná Delta area, which could not be assigned to previously described species. Among them, P. motoro is the most widely distributed species of the family Potamotrygonidae, present in most freshwater systems in South America [63,76,77]. The widespread distribution of the genera Potamotrygon, together with significant variation in some morphological characters (e.g., dorsal disc coloration) among populations of different basins, and even in closely adjacent areas, has led some authors to indicate that a taxonomic subdivision of P. motoro may be necessary [77,78]. In the case of Lower Paraná River stingrays, only COI sequences for P. motoro are available. Although low intra and interspecific variation have been reported among Potamotrygonidae family members in the Upper Paraná River basin [10,79,80], our results showed a high COI divergence between P. motoro specimens. This scenario claims a more extensive and profound taxonomic revision along with DNA sequences analysis for Potamotrygon genera that inhabits the Lower Parana River.
Results obtained in this work, and previous reports [10,11,22] state the existence of hidden diversity in many species and suggest that Neotropical species richness is still underestimated.

Importance of reference libraries
The success of using barcoding for species identification strongly depends on the presence of high-quality reference sequences available in public sequence libraries and the existence of specimen vouchers correctly identified. DNA barcode databases such as BOLD, have implemented minimal quality criteria for barcode data acquisition and generation [24]. However, reference specimen misidentification appears to be the single largest factor contributing to errors in the FISH-BOL data set [81]. Barcoding methodology and a careful examination of specimens allowed us to resolve apparent outliers and cluster conflicts in the FISH-BOL data set. This situation also highlights the importance of checking the taxonomic identity in the light of COI information previous to its upload in public sequence databases. This was the case for Brycon cf. hilarii, previously characterized as B. Orbignyanus, as well as for several detected BIN discordances based in misidentification. In these cases, the analyses of COI sequences correctly separates species pairs obtained in previous barcode studies on these species (e.g. Ageneiosus inermis vs. Ageneiosus ucayalensis [64]). COI sequence comparisons was not able to discriminate between two species of the genera Odontesthes (O. bonariensis and O. perugie). Moreover, shared haplotypes between specimens of both species were found (data not shown). This result is consistent with a recent radiation process in the genera Odontesthes as proposed by Garcia et al.  [82], and states that COI information could be used only for genera identification.
The current COI reference library provides highly reliable DNA and vouchers exemplars for 97.5% of the fish species investigated and it can be confidently used as a benchmark for identification of almost 50% of Lower Parana River fish species. This COI barcode library will be especially important for fish biodiversity monitoring, for sustainable exploitation of fishing resources, for reproductive biology studies and ecological monitoring, among other applications. Bootstrap values for 1000 replicates are shown at each branch. The number of specimens analyzed for each species is shown between brackets. Solid triangles represent clusters of multiple specimens, with height proportional to specimen number and the horizontal depth proportional to the genetic variation within each cluster. (TIF) S1 Table. Taxonomic classification of the 79 morphologically identified freshwater fish species from the Lower Paraná River in Argentina. (DOCX) S2 Table. List of species with "no true" discordance BINs found by the 'BIN Discordance Report' sequence analysis tool. Only BINs with species level conflicts are shown. (DOCX)