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Article

Molecular Data Reveal Multiple Lineages in Piranhas of the Genus Pygocentrus (Teleostei, Characiformes)

Departamento de Morfologia, Instituto de Biociências, Universidade Estadual Paulista, Rua Professor Doutor Antônio Celso Wagner Zanin, 250, Rubião Junior, Botucatu, SP 18618-689, Brazil
*
Author to whom correspondence should be addressed.
Genes 2019, 10(5), 371; https://doi.org/10.3390/genes10050371
Submission received: 12 April 2019 / Revised: 9 May 2019 / Accepted: 13 May 2019 / Published: 15 May 2019

Abstract

:
Carnivorous piranhas are distributed in four serrasalmid genera including Pygocentrus, which inhabit major river basins of South America. While P. cariba and P. piraya are endemics of the Orinoco and São Francisco basins, respectively, P. nattereri is widely distributed across the Amazonas, Essequibo, lower Paraná, Paraguay, and coastal rivers of northeastern Brazil, with recent records of introductions in Asia. Few studies have focused on the genetic diversity and systematics of Pygocentrus and the putative presence of additional species within P. nattereri has never been the subject of a detailed molecular study. Here we aimed to delimit species of Pygocentrus, test the phylogeographic structure of P. nattereri, and access the origin of introduced specimens of P. nattereri in Asia. Phylogenetic analyses based on a mitochondrial dataset involving maximum-likelihood tree reconstruction, genetic distances, Bayesian analysis, three delimitation approaches, and haplotype analysis corroborate the morphological hypothesis of the occurrence of three species of Pygocentrus. However, we provide here strong evidence that P. nattereri contains at least five phylogeographically-structured lineages in the Amazonas, Guaporé (type locality), Itapecuru, Paraná/Paraguay, and Tocantins/Araguaia river basins. We finally found that the introduced specimens in Asia consistently descend from the lineage of P. nattereri from the main Rio Amazonas. These results contribute to future research aimed to detect morphological variation that may occur in those genetic lineages of Pygocentrus.

1. Introduction

The Neotropical fish family Serrasalmidae contains 16 genera and 97 valid species [1] of ecomorphologically diverse freshwater fishes popularly known as pacus and piranhas. The species are divided in three main clades being two encompassed by pacus, tambaquis and silverdollars and a third containing mostly carnivorous piranhas [2]. This later clade includes six genera: the four carnivorous genera Pristobrycon Eigenmann, 1915, Pygocentrus Müller & Troschel, 1844, Pygopristis Müller & Troschel, 1844, and Serrasalmus Lacepède, 1803, the lepidophagous genus Catoprion Müller & Troschel, 1844 and the omnivorous Metynnis Cope 1878 [2,3,4]. The monophyly of this six-genera group is supported on the basis of both morphological [3,4] and multilocus molecular data [2,5,6].
The genus Pygocentrus includes the largest species of piranhas, reaching up to 50 cm standard length [7], that are highly appreciated in the ornamental trade and have a relative economic importance in regional fisheries and aquaculture [8,9]. Species of Pygocentrus are morphologically distinguished from other serrasalmids by a substantially wider head, a dorsal profile that is moderately to strongly convex, the presence of a preanal spine that is often undetectable externally, tricuspid teeth and the lack of ectopterygoid teeth, except in small juveniles [10,11]. The main synapomorphy of the genus is the presence of crests around the lateral-sensorial system of the frontal, parietal and pterotic bones [12]. The genus is monophyletic and hypothesized to be the sister clade of Serrasalmus plus Pristobrycon calmoni [2,13].
The taxonomic revision of Pygocentrus [10] recognized three species: P. cariba (Humboldt, 1821), an endemic from the Río Orinoco basin; P. nattereri Kner, 1858, widely-distributed in the Amazonas, Guianas, lower Paraná, Paraguay, and coastal rivers of northeastern Brazil; and P. piraya (Cuvier, 1819), the type-species of the genus, endemic from the Rio São Francisco basin (Figure 1). Fink [10] and Fink and Zelditch [14] did not find morphological or morphometric evidence that would support additional species within P. nattereri, leaving two nominal species in synonymy of P. nattereri: P. altus Gill, 1871, from the Río Marañon, upper Rio Amazonas, and P. ternetzi (Steindachner, 1908), from the Rio Paraguay. The three-species hypothesis were only recently tested in a broader barcoding study of the entire family Serrasalmidae that recognized both P. cariba and P. piraya but presented variable numbers of entities within P. nattereri depending on the delimitation analyses [15]. These analytical inconsistencies and the limited taxon sampling from relatively few Amazonian regions indicate the necessity of an intrageneric analysis to refine the species delimitation analyses, including samples from multiple South American river basins.
The variable number of species delimited for the red-bellied piranha Pygocentrus nattereri [15] is hypothesized by the genetic structure of lineages from distinct river systems. For example, the phylogeographic study of Pygocentrus based on the mtDNA control region found P. nattereri with structured genetic lineages in which the Paraná, Ucayali and Madeira lineages appeared genetically closer to each other than to the lineage from mainstream Rio Amazonas [13]. Population genetic studies within P. nattereri from the northeastern Brazil [16] and from the Rio Solimões/Amazonas [17] have also shown high levels of genetic diversity and significant genetic differentiation among populations. The maintenance of P. nattereri in captivity likely enabled the introduction of P. nattereri in several Asian rivers including in Bangladesh [18], China [9] and the Philippines [19,20]. However, studies reporting introductions lack evidence for the precise geographic origin of those parental specimens in South America.
Here, we used partial sequences of the mitochondrial gene cytochrome c oxidase subunit I (COI) and modern phylogenetic and species delimitation methods in order to (1) test the morphological hypothesis of the presence of three species of Pygocentrus [10], (2) test the population genetic hypothesis of multiple genetically-structured populations of P. nattereri [13,16,17], and (3) determine the geographic origin of recently introduced specimens of P. nattereri in Asia [20].

2. Materials and Methods

2.1. Taxon Sampling

Specimens were collected or obtained from fish collections, and morphologically identified by consulting the taxonomic literature and identification keys [10]. Specimens of the three valid species of Pygocentrus plus Serrasalmus elongatus Kner, 1858 as outgroup (root) were included in the analysis (Appendix A; Figure 2). The matrix contained 161 specimens, in which 57 were newly sequenced and 104 were obtained from GenBank (ncbi.nlm.nih.gov/genbank) or BOLD (boldsystems.org) databases (Appendix A). We attempted to obtain samples from all river basins in order to sample intraspecific genetic diversity for each species. We also included available sequences of P. nattereri introduced in the Philippines [20], the only available sequences on GenBank, to identify the original region that served as the source of those introduced specimens. Vouchers were fixed in 95% ethanol or 10% formalin and transferred to 70% ethanol for permanent storage and posteriorly deposited in the Laboratório de Biologia e Genética de Peixes, Universidade Estadual Paulista, Botucatu, Brazil (LBP), and Colección de Zoología, Universidad del Tolima, Ibagué, Colombia (CZUT-IC) (Appendix A).

2.2. DNA Extraction, Amplification and Sequencing

Tissue samples were taken from livers, gills, fins or muscles. The total DNA was isolated using the Qiagen “DNeasy Blood & Tissue” (Qiagen, Hilden, Germany) kit according to manufacturer’s instructions. Partial segments of the COI gene were amplified by PCR using the primers Fish F1 (5′-TCAACCAACCACAAAGACATTGGCAC-3′) and Fish R1 (5′–TAGACTTCTGGGTGGCCAAAGAATCA–3′) [21]. The PCR was performed on a thermocycler with a final volume of 12 µL containing of 8.175 µL distilled water, 0.5 µL dNTP (8 mM), 1.25 µL 10× Taq buffer (500 mM KCl; 200 mM Tris-HCl), 0.375 µL of MgCl2, 0.25 µL of each primer (10 µM) and 0.2 µL of PHT Taq polymerase. PCR conditions consisted of an initial denaturation at 95 °C for 5 min, followed by 35 cycles including denaturation at 95 °C for 45 s, annealing at 52 °C for 45 s and extension at 68 °C for 120 s, and a final extension at 68 °C for 5 min. Amplified products were checked on 1% agarose gel.
Amplicons were then purified with ExoSAP-IT (USB Corporation, Cleveland, OH, USA) following the manufacturer’s protocol. The purified product was used as template to sequence both DNA strands. The cycle sequencing reaction was carried out using a BigDye Terminator v3.1 Cycle Sequencing Ready Reaction kit (Applied Biosystems, Austin, TX, USA) in a final volume of 7 µL containing 0.35 µL primer (10 mM), 1.05 µL buffer 5×, 0.7 µL BigDye mix, and 3.9 µL distilled water. The cycle sequencing conditions were initial denaturation at 96 °C for 2 min followed by 30 cycles of denaturation at 96 °C for 45 s, annealing at 50 °C for 60 s, and extension at 60 °C for 4 min. The sequencing products were then purified following the protocol suggested in the BigDye Terminator v3.1 Cycle Sequencing kit’s manual (Applied Biosystems). All samples were sequenced on an ABI 3130 Genetic Analyzer (Applied Biosystems) following the manufacturer’s instructions.

2.3. Species Delimitation Analyses

Sequences were assembled and edited in Geneious 4.8 [22] to obtain a single consensus sequence for each specimen and also to check for deletions, insertions, and stop codons. Then, sequences were aligned with Muscle algorithm [23], and the aligned matrix was tested for saturation in DAMBE v7 [24]. The TN93+I (Tamura-Nei + Invariant sites) was estimated as the best-fit model of nucleotide evolution for our data by PartitionFinder [25] and was used in programs containing such a model. Sequences were binned into groups according to a neighbor-joining tree using TN93 in MEGA X [26]; for example, subgroups of Pygocentrus nattereri were split in five drainage-groups (Amazonas, Guaporé, Itapecuru, Paraná-Paraguay, and Tocantins/Araguaia) to test the prior hypothesis of multiple structured populations. The Amazonas population includes samples from the entire basin, except for Guaporé and Tocantins-Araguaia river basins as determined by the distance analysis. Three approaches of genetic distances were obtained using the TN93 model in MEGA X: the overall mean distance, intraspecific distances, and interspecific distances. The neighbor-joining tree was then generated in MEGA and tested by 1000 bootstrap pseudoreplicates.
We used three distinct species delimitation methods (Poisson Tree Process, Automatic Barcode Gap Discovery, and General Mixed Yule Coalescent Model) for our dataset using either sequence-based estimations or topology-based analyses based on the maximum likelihood (ML) or Bayesian inference. The maximum likelihood (ML) analysis was performed in RAxML v7.2 [27] using the GTR-GAMMA model, a maximum parsimony starting tree, and a posteriori analysis of bootstrap with the autoMRE function [28]. The best ML tree was used as an input tree for the Poisson Tree Process (PTP) model, that delimits species using non-ultrametric trees, since the speciation rate is modeled directly by the number of nucleotide substitutions [29]. The analysis was performed with the PTP webserver (species.h-its.org/ptp) using 100,000 MCMC generations and a 0.1 burn-in rate as the default settings.
Secondly, we performed the Automatic Barcode Gap Discovery (ABGD) analysis, an automatic procedure that sorts sequences into hypothetical species based on the barcode gap [30]. It infers a model-based confidence limit for intraspecific divergence by detecting the barcode gap as the first significant gap beyond this limit and uses it to partition the data. Inference of the limit and gap detection are then recursively applied to previously obtained groups to get finer partitions until there is no further partitioning [30]. The analysis was performed at the ABGD webserver (wwwabi.snv.jussieu.fr/public/abgd/abgdweb.html) with the Kimura (K80; 2.0) distance model with X = 1.0, Pmin = 0.001 and Pmax = 0.05.
Finally, we ran the General Mixed Yule Coalescent model (GMYC), a likelihood method that delimits species by fitting within- and between species branching models to reconstructed gene trees [31]. Because GMYC requires no polytomies, DAMBE v7 [24] was used to remove duplicated haplotypes, which improves the algorithm and maximizes computational time analysis. Then, a Bayesian inference of phylogeny was estimated with a relaxed lognormal clock with a speciation birth-death model, on an arbitrary timescale, using BEAST v1.8.4 [32]. The nucleotide evolution model used to estimate the ultrametric tree was TN93+I as estimated by PartitionFinder [25]. A random tree was used as a starting tree for the MCMC searches with two independent runs of 500,000,000 generations, with trees sampled at every 50,000th generation. The distribution of log-likelihood scores was examined to determine the stationary phase for each search and to decide whether extra runs were required to achieve convergence using Tracer v1.7.1 [33]. All sampled topologies beneath the asymptote were discarded as part of a burn-in procedure (10%), and the remaining trees were used to construct a 50% majority-rule consensus tree in TreeAnnotator v1.8.4. The resulting tree was visualized in FigTree v1.4.3, and the resultant topology was implemented in the GMYC analysis. The GMYC delimitation analysis was performed at the webserver (species.h-its.org/gmyc) with a single threshold method and other parameters set as default.
We also used DnaSP v5 [34] to estimate the number of polymorphic sites, haplotype number and haplotype/nucleotide diversity (HD/Pi) and used PopART v1.7 [35] to run a median-joining analysis [36] and obtain a haplotype network. Finally, we used a PhyloMap-PTP tool [37] available in the PTP webserver that combines Principal Coordinates Analysis (PCoA), PTP, and species tree mapping. These approaches were applied to understand the spatial distribution of haplotypes and how they are related to each other.

3. Results

Newly generated sequences were obtained from 57 specimens in addition to 104 sequences obtained from public databases, resulting in a final matrix with 161 sequences. Sequences are deposited in BOLD PYGO001-18–048-18 and PYGO049-19–057-19. Stop codons, deletions or insertions were absent in all sequences. Following alignment and editing, the final matrix has 522 bp of which 476 bp were conserved (91.2%) and 46 were variable, with 22.6% adenine, 31.8% cytosine, 27.9% thymine and 17.8% guanine. DAMBE revealed Iss values lower than Iss.cAsym and Iss.cSym values, which mean the lack of a saturation signal in the matrix. The dataset contains a total of 12 haplotypes (Pi = 12.157; HD = 0.835): one haplotype of Serrasalmus as root and 11 haplotypes of Pygocentrus. Pygocentrus cariba presented two haplotypes, P. piraya presented four haplotypes, and P. nattereri presented six haplotypes. Within P. nattereri, each sample from Amazonas, Guaporé, Itapecuru, Paraná/Paraguay and Tocantins/Araguaia presented exclusive haplotypes.
The genetic distance analysis recognizes the three morphologically-defined species of Pygocentrus with 0.059 ± 0.010 of distance between P. cariba and P. piraya, 0.055 ± 0.010 between P. cariba and P. nattereri, and 0.026 ± 0.006 between P. piraya and P. nattereri. Subgroups of P. nattereri presented genetic distances ranging from 0.005 ± 0.003 between Guaporé and Paraná/Paraguay to 0.017 ± 0.005 between Itapecuru and Tocantins/Araguaia and Itapecuru and Guaporé (Table 1). Results also reveal low intraspecific genetic variation within each lineage (0.000–0.003) (Table 1).
All topologies returned very similar results regarding the position of each lineage. Neighbor-joining (Figure S1), ML (Figure 3 and Figure S2) and the Bayesian tree (Figure S3) recognized each of the three previously recognized species of Pygocentrus and also indicates a clear segmentation of lineages in P. nattereri (Figure 3). The PTP method returned well-defined lineages for P. cariba and P. piraya and splitted P. nattereri in five distinct lineages from Amazonas, Guaporé, Itapecuru, Paraná/Paraguay, and Tocantins/Araguaia. The ABGD method resulted in eight partitions that ranged from 11 (p = 0.001) to two lineages (p = 0.02), with three partitions supporting the presence of seven lineages of Pygocentrus (p = 0.002–0.005), that is P. cariba, P. piraya, and P. nattereri subdivided in five subgroups: Amazonas, Guaporé, Itapecuru, Paraná/Paraguay and Tocantins/Araguaia. The GMYC oversplitted Pygocentrus in 16 lineages, two for P. cariba, five for P. piraya and eight for P. nattereri (three in the Amazonas, two in the Tocantins/Araguaia, and one for each Guaporé, Itapecuru, and Paraná/Paraguay). The threshold time obtained in the GMYC analysis was −1.14 × 10−4T, where T is the time from present to the time of the root.
Additionally, we included seven sequences of introduced specimens of Pygocentrus nattereri in the Philippines [20] to determine the source of parental specimens that were originally from South America. All topologies evidenced that they are genetically proximate to the Amazonas group (Figures S1 and S2). The sequences of specimens from Philippines (FCOD numbers) do not have any nucleotide substitution when compared to those collected in the Amazonas drainages (i.e., 0.000 genetic distance). This evidence indicates that the introduced specimens were obtained from somewhere in the Amazonas basin other than in the Guaporé or Tocantins/Araguaia or any other South American drainage. Haplotype network and PhyloMap-PTP approaches allow the visualization of the distribution and relationships of each haplotype (Figure 4).

4. Discussion

Species delimitation results support the recognition of the two species Pygocentrus cariba (Río Orinoco) and P. piraya (Rio São Francisco), and reveal the presence of five genetic lineages within the widely distributed P. nattereri. The three methods (PTP, ABGD and GMYC) split P. nattereri into five lineages: Amazonas, Guaporé, Itapecuru, Paraná/Paraguay, and Tocantins/Araguaia, and with GMYC splitting P. cariba and P. piraya in two and five entities in the Orinoco and São Francisco basins, respectively. After the examination of voucher specimens using traditional morphometric/meristic data for Serrasalmidae [38], we did not identify morphological variation or diagnoses to formally describe these genetic lineages (or potential species). Thus, we recognize the three current species of Pygocentrus and the presence of five structured populations of P. nattereri in South America. These lineages can be potentially sibling species sensu Mayr [39], representing the herein named P. nattereri species complex. Sibling species represent a special case of cryptic species, when they are closest relatives and are not distinguished from one another, taxonomically [39,40]. Similarly, recent studies have been revealed several examples of cryptic species in Neotropical freshwater fish, mostly due to advances in molecular systematics and integrative taxonomy [41,42,43].
Pygocentrus nattereri is the most abundant and widely distributed species of Pygocentrus and, accordingly, has controversial species boundaries and carries a history of doubts about its diagnostic features, validity and taxonomic status. Fink [10] performed a revision of Pygocentrus and could not find any exclusive character supporting its species status, despite analyzing P. nattereri from all drainages. However, he delimited P. nattereri by the combination of characters such as absence of humeral blotch in adults and lack of rays in the adipose fin. Type specimens of P. nattereri were assigned to rio Guaporé of the rio Madeira basin [10] and two names currently in synonym of P. nattereri are available for Pygocentrus: P. altus from the upper Rio Amazonas that could be applied for the Amazonas lineage, and P. ternetzi from the Rio Paraguay that could be applied for the Paraná/Paraguay lineage. However, we consider prematurely revalidating those species without a taxonomic revision, taking into account our strong molecular evidence for the occurrence of additional lineages within the present concept of P. nattereri.
Our results agree with the most recent barcoding study of the family Serrasalmidae that included all species of Pygocentrus [15] and recognized both P. cariba and P. piraya as two species, with segmentation of P. nattereri in multiple lineages depending on the delimitation approach. The authors [15] found two well-defined lineages of P. nattereri (Tocantins/Araguaia lineage, and Branco/Madeira/Tapajós lineage) with GMYC recognizing a third lineage from the Rio Guaporé (Madeira basin). Our results indicate those same clusters and added two additional ones: the Itapecuru and Paraná/Paraguay lineages (Figure 3). Present data also support the previous phylogeographic hypothesis that P. nattereri contains structured populations along the wide continental distribution [10,13] and also delimit each genetic lineage along the distribution of the species. It is noteworthy that additional samples from Guianas and other remote regions of Amazonia can be added to our dataset to further delimit P. nattereri.
Results presented herein indicate a very low genetic variation among most species of Pygocentrus, evident in P. piraya and within the P. nattereri complex, as exemplified by the low genetic distance values (Table 1) and the presence of few haplotypes even including species from a broad geographic expanse (Figure 4). For example, we identified an exclusive haplotype that is shared between specimens of P. nattereri collected in the Rio Solimões at Brazil/Colombia boundary and from Amapá lakes at the northern Amazonas estuary. Pygocentrus cariba presents the highest genetic distance values among Pygocentrus species, even more than S. elongatus with other Pygocentrus. In fact, Hubert et al. [13] found a rapid speciation between P. cariba and the ancestor of P. nattereri and P. piraya less than one million year after the split between Pygocentrus and Serrasalmus (~8.73 Ma vs. 8.0 Ma). On the other hand, the cladogenetic events leading to P. nattereri and P. piraya were much more recent at around 2.63 ± 0.2 Ma, the split of P. nattereri from the Amazonas and that from the upper Paraguay at around 1.8 Ma and that from the Paraná at about 1.77 ± 0.3 Ma, and the differentiation of the lineages from the upper Amazonas (Ucayali and Madeira) at around 0.79 ± 0.1 Ma, which suggest a rapid and relatively recent differentiation of P. nattereri and P. piraya lineages. Accordingly, Machado et al. [15] found P. cariba to be the first species to diverge from any other species of Pygocentrus or Serrasalmus.
Species of Pygocentrus are widely introduced outside their native ranges and the environment impacts are specially related to predation of native species and damage of fishing nets and other fishes [44,45]. Herein, sequences of Pygocentrus introduced in the Philippines [20] were included in the analyses and results indicate that they belong to the Amazonas lineage. The effects of an invasion can be both observed on single or small groups of species or through an entire ecosystem; impacts such as predation, herbivory, parasitism, disease, competition and hybridization led to extirpation or reduction of the local population, or even causing global extinction of native species [46]. The recognition of the invasive species is the first step towards the investigation and management actions that may follow, such as eradication, maintenance management and control of population density [46]. Since the effects of introduction of these specimens may lead to ecological damage (e.g., competition for food, space and spawning sites), the accurate information about origin of introduced specimens of P. nattereri might contribute for future local management purposes.
Morphological characters are traditionally used to discriminate Serrasalmidae species despite allometry and body coloration being highly variable during ontogeny, thus strongly affecting accurate species identifications [10]. The combination of morphological and molecular approaches appears to be a good point to study interspecific variation and, indeed, has helped to identify, discriminate and describe species of other serrasalmid genera. For example, the study including three recognized species of Mylossoma indicated five genetic lineages instead [47], with two species resurrected and redescribed afterwards (M. albiscopum and M. unimaculatum; [48]). In a similar vein, Andrade et al. [49] recognized the seventh species of Tometes by integrating both morphological and mitochondrial data. The results presented herein integrate these two studies and expand the promising field of integrative taxonomy of Serrasalmidae. Together, these studies indicate the need for deep revisions of species and genera of Serrasalmidae, involving both genetic and morphological data to determine the presence of potential undescribed species and to reassign species among genera. In this context, further research can address additional morphological characters in order to test our molecular hypothesis of the presence of seven genetic lineages of Pygocentrus in South America that can be potentially be recognized as valid species.

Supplementary Materials

The following are available online at https://www.mdpi.com/2073-4425/10/5/371/s1, Figure S1: Neighbor joining tree based on the cytochrome c oxidase I gene for Pygocentrus species. Figure S2: Maximum likelihood tree based on the cytochrome c oxidase I gene for Pygocentrus species Figure S3: Bayesian inference tree based on the cytochrome c oxidase I gene for Pygocentrus species.

Author Contributions

Conceptualization, N.T.B.M. and B.F.M.; methodology, N.T.B.M.; validation, N.T.B.M.; formal analysis, N.T.B.M. and B.F.M.; investigation, N.T.B.M.; resources, F.F. and C.O.; data curation, N.T.B.M. and C.O.; writing—original draft preparation, N.T.B.M.; writing—review and editing, N.T.B.M., B.F.M., F.F. and C.O.; visualization, N.T.B.M. and B.F.M.; supervision, F.F. and C.O.; project administration, N.T.B.M.; funding acquisition, N.T.B.M., F.F. and C.O.

Funding

Phylogenetic analyses were mostly performed on Brycon server at IBB/UNESP funded by FAPESP grant 2014/26508-3. Research was funded by Brazilian agencies CNPq 164213/2015-5 (NTBM), CNPq 404991/2018-1 (BFM), and CNPq 306054/2006-0 (CO). FAPESP 2016/11313-8 (BFM), and FAPESP 2014/26508-3 (CO).

Acknowledgments

The authors are grateful to Francisco Villa-Navarro (CZUT-IC) for the loan of important tissues, to Alec Zeinad for live images of Pygocentrus nattereri and P. piraya, and to Rafaela P. Ota for several discussions and comments on earlier versions of this paper.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table A1. Voucher, locality information and BOLD or Genbank accession numbers of the analyzed specimens of Pygocentrus.
Table A1. Voucher, locality information and BOLD or Genbank accession numbers of the analyzed specimens of Pygocentrus.
HaplotypeTaxonVoucherSpecimenLocality, BasinCity, StateCountryAccession n.
1P. caribaLBP 222915663Río Orinoco basinCaicara del Orinoco, BolívarVenezuelaPYGO003-18
1P. caribaLBP 222915664Río Orinoco basinCaicara del Orinoco, BolívarVenezuelaPYGO004-18
1P. caribaLBP 222915666Río Orinoco basinCaicara del Orinoco, BolívarVenezuelaPYGO005-18
1P. caribaLBP 229015815Río Orinoco basinCaicara del Orinoco, BolívarVenezuelaPYGO006-18
1P. caribaLBP 1022543107Río Apure, Orinoco basinCabruta, GuaricoVenezuelaPYGO001-18
1P. caribaLBP 1022543108Río Apure, Orinoco basinCabruta, GuaricoVenezuelaPYGO002-18
1P. caribaCZUT-IC 12810836Río Ariporo, Orinoco basin-ColombiaPYGO054-19
1P. caribaCZUT-IC 11395951Caño Materro, Orinoco basin-ColombiaPYGO052-19
2P. caribaUFAM 1352513525Río Orinoco basinGuainíaColombiaMG752525
1P. caribaUFAM 1352613526Río Orinoco basinGuainíaColombiaMG752526
1P. caribaUFAM 1352913529Río Orinoco basinGuainíaColombiaMG752527
1P. caribaUFAM 1374113741Río Orinoco basinGuainíaColombiaMG752528
1P. caribaUFAM 1374313743Río Orinoco basinGuainíaColombiaMG752529
1P. caribaUFAM 1374413744Río Orinoco basinGuainíaColombiaMG752530
1P. caribaUFAM 1374513745Río Orinoco basinGuainíaColombiaMG752531
6P. nattereriINPA 41663102036Rio Purus, Amazon basinAmazonasBrazilMG752578
6P. nattereriINPA 41689102084Rio Purus, Amazon basinAmazonasBrazilMG752579
6P. nattereriINPA 41689102085Rio Purus, Amazon basinAmazonasBrazilMG752580
6P. nattereriINPA 50418105742Rio Trombetas, Amazon basinParáBrazilMG752581
6P. nattereriINPA 50175105817Rio Trombetas, Amazon basinParáBrazilMG752582
6P. nattereriLBP 169712780Lago do Vanico, Amazon basinCarero, AmazonasBrazilPYGO031-18
6P. nattereriLBP 169712781Lago do Vanico, Amazon basinCarero, AmazonasBrazilPYGO032-18
9P. nattereriLBP 297819616Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO014-18
9P. nattereriLBP 297819617Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO015-18
9P. nattereriLBP 297819618Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO016-18
9P. nattereriLBP 297819619Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO017-8
9P. nattereriLBP 297819620Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO018-18
9P. nattereriLBP 400023086Rio Araguaia, Amazon basinS. Félix Araguaia, Mato GrossoBrazilPYGO011-18
9P. nattereriLBP 400023087Rio Araguaia, Amazon basinS. Félix Araguaia, Mato GrossoBrazilPYGO012-18
9P. nattereriLBP 400023091Rio Araguaia, Amazon basinS. Félix Araguaia, Mato GrossoBrazilPYGO013-18
10P. nattereriLBP 1264147072Rio Cuiabá, Paraguay basinCorumbá, Mato Grosso do SulBrazilPYGO022-18
9P. nattereriLBP 1269343551Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO019-18
9P. nattereriLBP 1269343552Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO020-18
9P. nattereriLBP 1269343554Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO021-18
9P. nattereriLBP 1273841012Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO007-18
9P. nattereriLBP 1273841050Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO008-18
9P. nattereriLBP 1273841051Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO009-18
9P. nattereriLBP 1273841053Rio Araguaia, Amazon basinCocalinho, Mato GrossoBrazilPYGO010-18
10P. nattereriLBP 1996179280Rio Paraná, lower Paraná basinCorateiParaguayPYGO023-18
6P. nattereriLBP 2183683905Rio Negro, Amazon basinManaus, AmazonasBrazilPYGO024-18
6P. nattereriLBP 2183683906Rio Negro, Amazon basinManaus, AmazonasBrazilPYGO025-18
6P. nattereriLBP 2183683908Rio Negro, Amazon basinManaus, AmazonasBrazilPYGO026-18
6P. nattereriLBP 2183683961Rio Negro, Amazon basinManaus, AmazonasBrazilPYGO027-18
6P. nattereriLBP 2232886477Rio Solimões, Amazon basinTabatinga, AmazonasBrazilPYGO028-18
6P. nattereriLBP 2232886478Rio Solimões, Amazon basinTabatinga, AmazonasBrazilPYGO029-18
6P. nattereriLBP 2232886479Rio Solimões, Amazon basinTabatinga, AmazonasBrazilPYGO030-18
6P. nattereriLBP 2065181252Lago Pracuúba, Atlantic drainagePracuúba, AmapáBrazilPYGO033-18
6P. nattereriLBP 2065181255Lago Pracuúba, Atlantic drainagePracuúba, AmapáBrazilPYGO034-18
6P. nattereriLBP 2097781157Rio Jari, Amazon basinAlmeirim, ParáBrazilPYGO035-18
6P. nattereriLBP 2097781161Rio Jari, Amazon basinAlmeirim, ParáBrazilPYGO036-18
6P. nattereriLBP 2281587632Rio Solimões, Amazon basinIranduba, AmazonasBrazilPYGO051-19
6P. nattereriLBP 2281587633Rio Solimões, Amazon basinIranduba, AmazonasBrazilPYGO050-19
6P. nattereriLBP 2281587634Rio Solimões, Amazon basinIranduba, AmazonasBrazilPYGO049-19
10P. nattereriNtrMS01-Rio Paraguay basinUnknownBrazilKP256424
10P. nattereriNtrMS02-Rio Paraguay basinUnknownBrazilKP256425
10P. nattereriNtrMS10-Rio Paraguay basinUnknownBrazilKP256426
10P. nattereriNtrMS11-Rio Paraguay basinUnknownBrazilKP256427
9P. nattereriNtrTO19-Rio Tocantins basinUnknownBrazilKP256428
9P. nattereriNtrTO21-Rio Tocantins basinUnknownBrazilKP256429
9P. nattereriNtrTO24-Rio Tocantins basinUnknownBrazilKP256430
9P. nattereriNtrTO30-Rio Tocantins basinUnknownBrazilKP256431
10P. nattereriOL-0485-UnknownUnknownUnknownDSFRE372-08
10P. nattereriOL-0486-UnknownUnknownUnknownDSFRE373-08
10P. nattereriOL-0487-UnknownUnknownUnknownDSFRE374-08
6P. nattereriP1A-Introduced specimensMetro ManilaPhilippinesFCOD001-15
6P. nattereriP1B-Introduced specimensMetro ManilaPhilippinesFCOD002-15
6P. nattereriP1C-Introduced specimensMetro ManilaPhilippinesFCOD003-15
6P. nattereriP2C-Introduced specimensMetro ManilaPhilippinesFCOD006-15
6P. nattereriP3A-Introduced specimensMetro ManilaPhilippinesFCOD007-15
6P. nattereriP3B-Introduced specimensMetro ManilaPhilippinesFCOD008-15
6P. nattereriP3C-Introduced specimensMetro ManilaPhilippinesFCOD009-15
6P. nattereriNC_015840-UnknownUnknownUnknownNC015840
8P. nattereriUEMA 104549-Rio Itapecuru basinRosário, MaranhãoBrazilITAPE137-15
8P. nattereriUEMA 104549-Rio Itapecuru basinRosário, MaranhãoBrazilITAPE138-15
8P. nattereriUEMA 104549-Rio Itapecuru basinRosário, MaranhãoBrazilITAPE139-15
8P. nattereriUEMA 104549-Rio Itapecuru basinRosário, MaranhãoBrazilITAPE140-15
8P. nattereriUEMA 104549-Rio Itapecuru basinRosário, MaranhãoBrazilITAPE141-15
8P. nattereriUEMA 104549-Rio Itapecuru basinRosário, MaranhãoBrazilITAPE142-15
8P. nattereriUEMA 104549-Rio Itapecuru basinItapecuru Mirim, MaranhãoBrazilITAPE144-15
8P. nattereriUEMA 104549-Rio Itapecuru basinItapecuru Mirim, MaranhãoBrazilITAPE145-15
8P. nattereriUEMA 104549-Rio Itapecuru basinItapecuru Mirim, MaranhãoBrazilITAPE146-15
8P. nattereriUEMA 104550-Rio Itapecuru basinMirador, MaranhãoBrazilITAPE148-15
8P. nattereriUEMA 104550-Rio Itapecuru basinMirador, MaranhãoBrazilITAPE149-15
8P. nattereriUEMA 104550-Rio Itapecuru basinMirador, MaranhãoBrazilITAPE150-15
6P. nattereriUFAM 643643Rio Amazonas basinParáBrazilMG752532
6P. nattereriUFAM 644644Rio Amazonas basinParáBrazilMG752533
9P. nattereriUFAM 29312931Rio Araguaia basinParáBrazilMG752534
9P. nattereriUFAM 29322932Rio Araguaia basinParáBrazilMG752535
9P. nattereriUFAM 29332933Rio Araguaia basinParáBrazilMG752536
6P. nattereriUFAM 35793579Rio Amazonas basinAmazonasBrazilMG752537
6P. nattereriUFAM 35803580Rio Amazonas basinAmazonasBrazilMG752538
6P. nattereriUFAM 35813581Rio Amazonas basinAmazonasBrazilMG752539
6P. nattereriUFAM 38293829Rio Paru, Amazon basinParáBrazilMG752542
6P. nattereriUFAM 38303830Rio Paru, Amazon basinParáBrazilMG752543
6P. nattereriUFAM 38313831Rio Paru, Amazon basinParáBrazilMG752544
9P. nattereriUFAM 39033903Rio Tocantins basinParáBrazilMG752545
9P. nattereriUFAM 39043904Rio Tocantins basinParáBrazilMG752546
9P. nattereriUFAM 39053905Rio Tocantins basinParáBrazilMG752547
9P. nattereriUFAM 45564556Rio Tocantins basinParáBrazilMG752548
9P. nattereriUFAM 45574557Rio Tocantins basinParáBrazilMG752549
9P. nattereriUFAM 45584558Rio Tocantins basinParáBrazilMG752550
6P. nattereriUFAM 55535553Rio Xingu, Amazon basinParáBrazilMG752551
6P. nattereriUFAM 1149711497Rio Tapajós, Amazon basinParáBrazilMG752553
6P. nattereriUFAM 1149811498Rio Tapajós, Amazon basinParáBrazilMG752554
6P. nattereriUFAM 1150011500Rio Tapajós, Amazon basinParáBrazilMG752556
6P. nattereriUFAM 1150111501Rio Tapajós, Amazon basinParáBrazilMG752557
6P. nattereriUFAM 1260312603Rio Branco, Amazon basinRoraimaBrazilMG752558
6P. nattereriUFAM 1262612626Rio Branco, Amazon basinRoraimaBrazilMG752559
6P. nattereriUFAM 1410514105Rio Branco, Amazon basinRoraimaBrazilMG752560
6P. nattereriUFAM 1410614106Rio Branco, Amazon basinRoraimaBrazilMG752561
6P. nattereriUFAM 1410714107Rio Branco, Amazon basinRoraimaBrazilMG752562
6P. nattereriUFAM 1410814108Rio Branco, Amazon basinRoraimaBrazilMG752563
6P. nattereriUFAM 1526115261Rio Madeira, Amazon basinAmazonasBrazilMG752564
6P. nattereriUFAM 1526215262Rio Madeira, Amazon basinAmazonasBrazilMG752565
6P. nattereriUFAM 1526315263Rio Madeira, Amazon basinAmazonasBrazilMG752566
11P. nattereriUFAM 1527215272Rio Guaporé, Amazon basinRondôniaBrazilMG752567
11P. nattereriUFAM 1527315273Rio Guaporé, Amazon basinRondôniaBrazilMG752568
11P. nattereriUFAM 1527415274Rio Guaporé, Amazon basinRondôniaBrazilMG752569
11P. nattereriUFAM 1527615276Rio Guaporé, Amazon basinRondôniaBrazilMG752570
11P. nattereriUFAM 1527815278Rio Guaporé, Amazon basinRondôniaBrazilMG752572
4P. pirayaINPA 5674115283Rio São Francisco basinMinas Gerais/BahiaBrazilMG752583
4P. pirayaINPA 5674115284Rio São Francisco basinMinas Gerais/BahiaBrazilMG752584
4P. pirayaINPA 5674115285Rio São Francisco basinMinas Gerais/BahiaBrazilMG752585
3P. pirayaLBP 1128648749Rio São Francisco basinGararu, SergipeBrazilPYGO037-18
4P. pirayaLBP 1128648750Rio São Francisco basinGararu, SergipeBrazilPYGO038-18
3P. pirayaLBP 1128648751Rio São Francisco basinGararu, SergipeBrazilPYGO039-18
5P. pirayaLBP 1130042931Rio São Francisco basinS. Roque Minas, Minas GeraisBrazilPYGO046-18
7P. pirayaLBP 1133645522Rio São Francisco basinS. Roque Minas, Minas GeraisBrazilPYGO047-18
3P. pirayaLBP 1133745546Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO055-19
4P. pirayaLBP 1133745547Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO057-19
4P. pirayaLBP 1133745548Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO056-19
3P. pirayaLBP 2161347336Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO040-18
3P. pirayaLBP 2161347337Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO041-18
4P. pirayaLBP 2161347338Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO042-18
3P. pirayaLBP 2161347339Rio São Francisco basinPirapora, Minas GeraisBrazilPYGO043-18
3P. pirayaLBP 2161259752Rio São Francisco basinJenipatuba, Minas GeraisBrazilPYGO044-18
4P. pirayaLBP 2161259753Rio São Francisco basinJenipatuba, Minas GeraisBrazilPYGO045-18
3P. pirayaDCC502-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600843
4P. pirayaDCC503-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600844
4P. pirayaDCC499-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600845
3P. pirayaDCC501-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600846
3P. pirayaDCC532-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600847
4P. pirayaDCC500-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600848
3P. pirayaDCC306-Rio Pandeiros, São Francisco basinJanuária, Minas GeraisBrazilHQ600849
5P. pirayaDCC1043-Rio São Francisco basinVárzea da Palma, Minas GeraisBrazilHM405211
4P. pirayaPrySF499-Rio São Francisco basinUnknownBrazilKP256432
4P. pirayaPrySF500-Rio São Francisco basinUnknownBrazilKP256433
3P. pirayaPrySF501-Rio São Francisco basinUnknownBrazilKP256434
4P. pirayaPrySF503-Rio São Francisco basinUnknownBrazilKP256435
5P. piraya--UnknownUnknownUnknownDSFRE115-08
7P. piraya--UnknownUnknownUnknownDSFRE116-08
4P. piraya--UnknownUnknownUnknownDSFRE117-08
3P. piraya--UnknownUnknownUnknownDSFRE118-08
3P. piraya--UnknownUnknownUnknownDSFRE351-08
5P. piraya--UnknownUnknownUnknownDSFRE352-08
5P. piraya--UnknownUnknownUnknownDSFRE387-08
5P. piraya--UnknownUnknownUnknownDSFRE388-08
4P. pirayaUFAM 1528615286Rio São Francisco basinMinas Gerais/BahiaBrazilMG752586
3P. pirayaUFAM 1528715287Rio São Francisco basinMinas Gerais/BahiaBrazilMG752587
4P. pirayaUFAM 1528815288Rio São Francisco basinMinas Gerais/BahiaBrazilMG752588
3P. pirayaUFAM 1528915289Rio São Francisco basinMinas Gerais/BahiaBrazilMG752589
12S. elongatusUFAM 1526015260Rio Madeira basinAmazonasBrazilMG752622

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Figure 1. Representative specimens of Pygocentrus: (A) P. cariba, Río Apure, LBP 10225. (B) P. nattereri, Rio das Mortes, Araguaia basin. (C) P. piraya, Rio São Francisco. Photographs by Alec Zeinad (B,C), specimens not preserved.
Figure 1. Representative specimens of Pygocentrus: (A) P. cariba, Río Apure, LBP 10225. (B) P. nattereri, Rio das Mortes, Araguaia basin. (C) P. piraya, Rio São Francisco. Photographs by Alec Zeinad (B,C), specimens not preserved.
Genes 10 00371 g001
Figure 2. Distribution map of specimens of Pygocentrus. Different shades of blue represent distinct genetic lineages of P. nattereri found in this study.
Figure 2. Distribution map of specimens of Pygocentrus. Different shades of blue represent distinct genetic lineages of P. nattereri found in this study.
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Figure 3. Best maximum likelihood tree based on the cytochrome c oxidase subunit I gene for Pygocentrus species evidencing the presence of multiple genetic lineages within P. nattereri. Colored bars after tip names represents results of the three species delimitation analyses. GMYC results for the Amazonas lineage of P. nattereri are not delimited by taxa. Numbers near nodes indicate bootstrap support.
Figure 3. Best maximum likelihood tree based on the cytochrome c oxidase subunit I gene for Pygocentrus species evidencing the presence of multiple genetic lineages within P. nattereri. Colored bars after tip names represents results of the three species delimitation analyses. GMYC results for the Amazonas lineage of P. nattereri are not delimited by taxa. Numbers near nodes indicate bootstrap support.
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Figure 4. Haplotype network (above) and PhyloMap-PTP (below) showing the distribution of the 11 distinct haplotypes of Pygocentrus.
Figure 4. Haplotype network (above) and PhyloMap-PTP (below) showing the distribution of the 11 distinct haplotypes of Pygocentrus.
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Table 1. Pairwise TN93 genetic distance values among drainage-based lineages of Pygocentrus. Bold numbers represent intraspecific genetic variation. Amaz = Amazonas; Itapec = Itapecuru; Toc/Ara = Tocantins/Araguaia; Par/Par = Paraná/Paraguay; Guap = Guaporé.
Table 1. Pairwise TN93 genetic distance values among drainage-based lineages of Pygocentrus. Bold numbers represent intraspecific genetic variation. Amaz = Amazonas; Itapec = Itapecuru; Toc/Ara = Tocantins/Araguaia; Par/Par = Paraná/Paraguay; Guap = Guaporé.
P. caribaP. pirayaP. nattereri
Amaz
P. nattereri
Itapec
P. nattereri
Toc/Ara
P. nattereri
Par/Par
P. nattereri
Guap
S. elongatus
P. cariba0.000 ± 0.000
P. piraya0.059 ± 0.0100.003 ± 0.001
P. nattereri Amaz0.051 ± 0.0100.025 ± 0.0060.000 ± 0.000
P. nattereri Itapec0.056 ± 0.0100.035 ± 0.0080.009 ± 0.0040.000 ± 0.000
P. nattereri Toc/Ara0.056 ± 0.0100.027 ± 0.0070.011 ± 0.0040.017 ± 0.0050.000 ± 0.000
P. nattereri Par/Par0.045 ± 0.0090.019 ± 0.0050.009 ± 0.0040.015 ± 0.0050.011 ± 0.0040.000 ± 0.000
P. nattereri Guap0.050 ± 0.0090.017 ± 0.0050.007 ± 0.0030.017 ± 0.0050.009 ± 0.0390.005 ± 0.0030.000 ± 0.000
S. elongatus0.046 ± 0.0090.037 ± 0.0080.041 ± 0.0090.048 ± 0.0090.042 ± 0.0090.037 ± 0.0080.040 ± 0.008-

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Mateussi, N.T.B.; Melo, B.F.; Foresti, F.; Oliveira, C. Molecular Data Reveal Multiple Lineages in Piranhas of the Genus Pygocentrus (Teleostei, Characiformes). Genes 2019, 10, 371. https://doi.org/10.3390/genes10050371

AMA Style

Mateussi NTB, Melo BF, Foresti F, Oliveira C. Molecular Data Reveal Multiple Lineages in Piranhas of the Genus Pygocentrus (Teleostei, Characiformes). Genes. 2019; 10(5):371. https://doi.org/10.3390/genes10050371

Chicago/Turabian Style

Mateussi, Nadayca T.B., Bruno F. Melo, Fausto Foresti, and Claudio Oliveira. 2019. "Molecular Data Reveal Multiple Lineages in Piranhas of the Genus Pygocentrus (Teleostei, Characiformes)" Genes 10, no. 5: 371. https://doi.org/10.3390/genes10050371

APA Style

Mateussi, N. T. B., Melo, B. F., Foresti, F., & Oliveira, C. (2019). Molecular Data Reveal Multiple Lineages in Piranhas of the Genus Pygocentrus (Teleostei, Characiformes). Genes, 10(5), 371. https://doi.org/10.3390/genes10050371

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