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. 2017 Oct 12;8:149. doi: 10.3389/fgene.2017.00149

Revealing Hidden Diversity of the Underestimated Neotropical Ichthyofauna: DNA Barcoding in the Recently Described Genus Megaleporinus (Characiformes: Anostomidae)

Jorge L Ramirez 1,*, Jose L Birindelli 2, Daniel C Carvalho 3, Paulo R A M Affonso 4, Paulo C Venere 5, Hernán Ortega 6, Mauricio Carrillo-Avila 7, José A Rodríguez-Pulido 8, Pedro M Galetti Jr 1
PMCID: PMC5643504  PMID: 29075287

Abstract

Molecular studies have improved our knowledge on the neotropical ichthyofauna. DNA barcoding has successfully been used in fish species identification and in detecting cryptic diversity. Megaleporinus (Anostomidae) is a recently described freshwater fish genus within which taxonomic uncertainties remain. Here we assessed all nominal species of this genus using a DNA barcode approach (Cytochrome Oxidase subunit I) with a broad sampling to generate a reference library, characterize new molecular lineages, and test the hypothesis that some of the nominal species represent species complexes. The analyses identified 16 (ABGD and BIN) to 18 (ABGD, GMYC, and PTP) different molecular operational taxonomic units (MOTUs) within the 10 studied nominal species, indicating cryptic biodiversity and potential candidate species. Only Megaleporinus brinco, Megaleporinus garmani, and Megaleporinus elongatus showed correspondence between nominal species and MOTUs. Within six nominal species, a subdivision in two MOTUs was found, while Megaleporinus obtusidens was divided in three MOTUs, suggesting that DNA barcode is a very useful approach to identify the molecular lineages of Megaleporinus, even in the case of recent divergence (< 0.5 Ma). Our results thus provided molecular findings that can be used along with morphological traits to better define each species, including candidate new species. This is the most complete analysis of DNA barcode in this recently described genus, and considering its economic value, a precise species identification is quite desirable and fundamental for conservation of the whole biodiversity of this fish.

Keywords: cryptic species, freshwater fishes, allopatric speciation, South American basins, cytochrome oxidase subunit I

Introduction

Neotropical freshwater fishes have a remarkable diversity, exceeding 8000 species (Reis et al., 2016), however, much taxonomic uncertainty exists leading to underestimated diversity (Pereira et al., 2013; Reis et al., 2016). Molecular studies have been crucial to improve our knowledge on the ichthyofauna, and DNA barcoding has successfully been used in fish species identification and in detecting species of taxonomic concerns or cryptic diversity (Pereira et al., 2013; Gomes et al., 2015; Ramirez and Galetti, 2015; Machado et al., 2016). Within the neotropical freshwater fishes, the order Characiformes represents more than 30% of the known species, and Anostomidae is one of the most species-rich families, occurring in all major hydrographic basins, with trans- and cis-Andean distribution in South America (Reis et al., 2003).

Comprising approximately 150 described species, distributed in 15 genera (Garavello and Britski, 2003; Sidlauskas and Vari, 2008; Ramirez et al., 2017), the known diversity of the Anostomidae has increased in recent years. For instance, 14 species and 1 genus were described only in the last 5 years (Birindelli et al., 2013; Burns et al., 2014). DNA barcoding has revealed taxonomic uncertainties within the genus Laemolyta (Ramirez and Galetti, 2015), and molecular phylogeny has helped to provide an understanding of the evolutionary history of the Anostomidae (Ramirez and Galetti, 2015; Ramirez et al., 2016, 2017).

Recently, the genus Megaleporinus (Ramirez et al., 2017) was described to include 16 lineages, corresponding to 10 nominal species, previously recognized in Leporinus or Hypomasticus (Ramirez et al., 2017). Megaleporinus is supported by cytogenetic, molecular, and morphological data. It is characterized by having a unique ZZ/ZW sex chromosome system (Galetti et al., 1995), while most cytogenetically known Leporinus species have no sex chromosomes (Galetti et al., 1981, 1991). Its monophyly is also well supported by mitochondrial and nuclear markers, which identified it as the sister group to Abramites (Ramirez et al., 2017). Concerning its morphology, Megaleporinus is characterized by being relatively large (adults usually reaching more than 35 cm standard length, including the largest species of the family), three teeth on each premaxillary and dentary bones, and a color pattern of one to three dark mid-lateral blotches (Ramirez et al., 2017). Because of its large size, Megaleporinus has an economic importance in subsistence fisheries and aquaculture (Garavello and Britski, 2003).

Recent studies indicate that there is a hidden biodiversity within Megaleporinus that needs to be better understood (Avelino et al., 2015; Ramirez et al., 2017). A study based on mitochondrial and nuclear markers, but using few individuals for each species, showed that several nominal species allocated to this genus comprise two or more molecular lineages allopatrically distributed in different basins (Ramirez et al., 2017).

In this study, we used a DNA barcoding approach to generate a reference library for Megaleporinus, assessing all nominal species and lineages previously described. We included a broad sampling for most of the species. Our hypothesis is that DNA barcoding support the observation that some of the nominal species represent species complexes with most molecular operational taxonomic units (MOTUs) allopatrically distributed in different basins, as proposed by Ramirez et al. (2017). Identifying such hidden biodiversity within this genus, this paper will contribute to a more complete understanding of its diversity and to the conservation of this important fish group.

Materials and Methods

Sampling

Animals were collected on public land, handled and killed under permission (ICMBIO/MMA N° 32215) provided by the Environment Ministry (MMA). This study did not involve endangered or protected species. Fish were collected by fishing rods and gillnets. No ethics committee approval is required for these organisms in Brazil. Fish were killed in the field using cold water and immediately transferred onto ice. Tissue samples were collected after fish death was confirmed through lack of operculum movement.

Specimens from several populations of all Megaleporinus species were used in this study, totaling 79 samples of the 10 nominal species, and comprising the 16 molecular lineages described by Ramirez et al., 2017 (Figures 1, 2 and Table 1). Voucher numbers are provided for the specimens (Table 1). Additionally, previous DNA barcode sequences of specimens from the São Francisco (Carvalho et al., 2011), Paraná (Pereira et al., 2013), Paranapanema (Frantine-Silva et al., 2015), and lower Paraná basins (Díaz et al., 2016) were included in our data set giving a total of 116 sequences (Figures 1, 2 and Table 1).

FIGURE 1.

FIGURE 1

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Collection sites (circles) and hydrographic basin of occurrence of Megaleporinus MOTUs. Localities’ numbers according to Table 1.

FIGURE 2.

FIGURE 2

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Studied specimens of Megaleporinus. (A) M. brinco, MZUSP 118670; (B) M. cf. conirostris, LISDEBE 6971; (C) M. cf. muyscorum; (D) M. cf. obtusidens Paraguay, MZUSP 118668; (E) M. cf. obtusidens São Francisco, MCP 44805; (F) M. cf. reinhardti, UESB-8206; (G) M. cf. trifasciatus, GEPEMA 5095; (H) M. garmani, MCNI-PUCMG-0020; (I) M. macrocephalus, MZUSP 118667; (J) M. muyscorum, ICN-19074; (K) M. obtusidens, MZUSP 113982; (L) M. piavussu, MZUSP 113981; (M) M. reinhardti; (N) M. trifasciatus, MUSM – 47351. Scale bars equal 1 cm.

Table 1.

Sampling information and GenBank accession for specimens included in the analysis.

MOTU River (Locality) Basin BIN GenBank Museum ID
Megaleporinus brinco Contas12 Contas ADB0463 KU134850 MZUSP – 118670
M. brinco Contas12 Contas ADB0463 KX925449 MZUSP – 118670
M. brinco Contas12 Contas ADB0463 KX925450 MZUSP – 118670
M. cf. conirostris Doce (Governador Valadares)18 Doce ACL4264 KF568977 MCNI-PUCMG-0186
M. cf. conirostris Doce (Governador Valadares)18 Doce ACL4264 KX925451 –
M. cf. conirostris Doce (Governador Valadares)18 Doce ACL4264 KX925452 –
M. cf. conirostris Doce (Baixo Guandú)19 Doce ACL4264 KX925453 LISDEBE 6971
M. cf. muyscorum Meta (Puerto Lopez)2 Orinoco ADB0512 KU134851 –
M. cf. obtusidens Paraguay Cuiaba (Santo Antonio de Leverger)8 Paraguai ACL3942 KU134861 MZUSP – 118668
M. cf. obtusidens São Francisco São Francisco (Tres Marias)20 São Francisco ABZ0928 HM405029 ∗
M. cf. obtusidens São Francisco Pandeiros14 São Francisco ABZ0928 HM405142 ∗
M. cf. obtusidens São Francisco Urucuia (Urucuia)13 São Francisco ABZ0928 HM906022 ∗
M. cf. obtusidens São Francisco Urucuia (Urucuia)13 São Francisco ABZ0928 HM906023 ∗
M. cf. obtusidens São Francisco São Francisco (Tres Marias)16 São Francisco ABZ0928 HM405028 ∗
M. cf. obtusidens São Francisco São Francisco (Pirapora)27 São Francisco ABZ0928 KX925498 LISDEBE 6973
M. cf. obtusidens São Francisco São Francisco (Pirapora)27 São Francisco ABZ0928 KX925499 –
M. cf. obtusidens São Francisco São Francisco (Pirapora)27 São Francisco ABZ0928 KX925500 –
M. cf. obtusidens São Francisco São Francisco (Pirapora)27 São Francisco ABZ0928 KX925501 –
M. cf. obtusidens São Francisco São Francisco (Pirapora)27 São Francisco ABZ0928 KX925502 –
M. cf. obtusidens São Francisco Pandeiros (Pandeiros)14 São Francisco ABZ0928 KU134862 MCP – 44805
M. cf. obtusidens São Francisco Urucuia (Urucuia)13 São Francisco ABZ0928 KX925503 –
M. cf. obtusidens São Francisco Urucuia (Urucuia)13 São Francisco ABZ0928 KX925504 MCP – 44076
M. cf. reinhardti Itapicurú11 Itapicurú-mirim AAD1729 KU134849 –
M. cf. reinhardti Itapicurú11 Itapicurú-mirim AAD1729 KX925454 –
M. cf. reinhardti Itapicurú11 Itapicurú-mirim AAD1729 KX925455 –
M. cf. reinhardti Itapicurú11 Itapicurú-mirim AAD1729 KX925456 UESB-8206
M. cf. trifasciatus Araguaia (Ouro fino)10 Tocantins ACL3074 KX925457 GEPEMA – 4975
M. cf. trifasciatus Araguaia (Barra do Garças)10 Tocantins ACL3074 KF568998 GEPEMA – 5095
M. cf. trifasciatus Araguaia (Barra do Garças)10 Tocantins ACL3074 KX925458 GEPEMA – 5594
M. conirostris Paraibuna20 Paraiba do Sul ACL3731 KU134852 –
M. conirostris Paraibuna20 Paraiba do Sul ACL3731 KX925459 –
M. elongatus Itacambiruçu (Grão Mogol)15 Jequitinhonha ABY2894 KX925463 –
M. elongatus Itacambiruçu (Grão Mogol)15 Jequitinhonha ABY2894 KU134853 MCNI-PUCMG-0375
M. elongatus Jequitinhonha ABY2894 KX925464 MCNI-PUCMG-0221
M. elongatus Jequitinhonha (UHE Irapé)29 Jequitinhonha ABY2894 KU134854 –
M. elongatus Jequitinhonha (UHE Irapé)29 Jequitinhonha ABY2894 KX925465 MCNI-PUCMG-0299
M. elongatus Jequitinhonha (UHE Irapé)29 Jequitinhonha ABY2894 KX925466 MCNI-PUCMG-0300
M. elongatus Rio Pardo (Águas Vermelhas)28 Pardo ABY2894 KX925460 MCNI-PUCMG-4451
M. elongatus Rio Pardo (Águas vermelhas)28 Pardo ABY2894 KX925461 MCNI-PUCMG-5175
M. elongatus Rio Pardo (Águas vermelhas)28 Pardo ABY2894 KX925462 MCNI-PUCMG-5176
M. garmani Itacambiruçu (Grão Mogol)15 Jequitinhonha ACL3227 KU134855 MCNI-PUCMG-0021
M. garmani Itacambiruçu (Grão Mogol)15 Jequitinhonha ACL3227 KX925467 MCNI-PUCMG-0020
M. garmani Itacambiruçu (Grão Mogol)15 Jequitinhonha ACL3227 KX925468 MCNI-PUCMG-0021
M. garmani Itacambiruçu (Grão Mogol)15 Jequitinhonha ACL3227 KX925469 MCNI-PUCMG-0021
M. garmani Itacambiruçu (Grão Mogol)15 Jequitinhonha ACL3227 KX925470 MCNI-PUCMG-0374
M. macrocephalus Manhuaçu (São José do Mantimento) Doce AAE5328 KX925475 MCNI-PUCMG-0460
M. macrocephalus Cuiaba (Santo Antonio de Leverger)8 Paraguai AAE5328 KU134856 MZUSP – 118667
M. macrocephalus Cuiaba (Santo Antonio de Leverger)8 Paraguai AAE5328 KX925471 LISDEBE 6972
M. macrocephalus Cuiaba (Cuiaba)7 Paraguai AAE5328 KX925474 –
M. macrocephalus Cuiaba (Barão de Melgaço)9 Paraguai AAE5328 KX925476 LISDEBE 6974
M. macrocephalus Cuiaba (Barão de Melgaço)9 Paraguai AAE5328 KX925477 LISDEBE 6974
M. macrocephalus Tiete (Barra Bonita) Paraná AAE5328 KX925473 –
M. macrocephalus Pandeiros São Francisco AAE5328 HM906021 –
M. macrocephalus Araguaia (Ouro fino) Tocantins AAE5328 KX925472 GEPEMA – 4974
M. macrocephalus Paraná Cinzas (Bandeirantes)25 Paraná ACO1303 KM897611 ∗
M. macrocephalus Paraná Cinzas (Bandeirantes)25 Paraná ACO1303 KM897537 ∗
M. macrocephalus Paraná Cinzas (Bandeirantes)25 Paraná ACO1303 KM897575 ∗
M. macrocephalus Paraná Cinzas (Bandeirantes)25 Paraná ACO1303 KM897296 ∗
M. macrocephalus Paraná Piracicaba (Tamanduá)23 Paraná ACO1303 JN988999 LBPV-19469
M. muyscorum Magdalena (Neiva)1 Magdalena ADB0701 KX925478 ICN-19072
M. muyscorum Magdalena (Neiva)1 Magdalena ADB0701 KX925479 ICN-19073
M. muyscorum Magdalena (Neiva)1 Magdalena ADB0701 KU134857 ICN-19074
M. obtusidens Jacuí (Jacuizinho Foz)26 Jacuí AAB8578 KU134859 MCP-25476
M. obtusidens Piracicaba (Tamanduá)23 Paraná AAB8578 JN988985 LBPV-19849
M. obtusidens Piracicaba (Tamanduá)23 Paraná AAB8578 JN988984 LBPV-19850
M. obtusidens Piracicaba (Tamanduá)23 Paraná AAB8578 JN988983 LBPV-19852
M. obtusidens Paranapanema (Canoas)22 Paraná AAB8578 KM897227 ∗
M. obtusidens Paranapanema (Canoas)22 Paraná AAB8578 KM897138 ∗
M. obtusidens Paranapanema (Canoas)22 Paraná AAB8578 KM897434 ∗
M. obtusidens Cinzas (Bandeirantes)25 Paraná AAB8578 KM897597 ∗
M. obtusidens Turvo (Icem)21 Paraná AAB8578 KX925480 LISDEBE 6969
M. obtusidens Turvo (Icem)21 Paraná AAB8578 KX925481 –
M. obtusidens Turvo (Icem)21 Paraná AAB8578 KX925482 –
M. obtusidens Turvo (Icem)21 Paraná AAB8578 KX925483 –
M. obtusidens Turvo (Icem)21 Paraná AAB8578 KU134858 MZUSP – 113982
M. obtusidens Turvo (Icem)21 Paraná AAB8578 KF568987 –
M. obtusidens Paraná (Porto Camargo)24 Paraná AAB8578 KX925484 –
M. obtusidens Paraná (Porto Camargo)24 Paraná AAB8578 KX925485 –
M. obtusidens Ibicui (BR 472)25 Uruguay AAB8578 KU134860 MCP-28917
M. piavussu Piracicaba (Tamanduá)23 Paraná AAB8569 JN989005 LBPV-15587∗
M. piavussu Piracicaba (Tamanduá)23 Paraná AAB8569 JN989004 LBPV-19851∗
M. piavussu Piracicaba (Tamanduá)23 Paraná AAB8569 JN989003 LBPV-19854∗
M. piavussu Paranapanema (Canoas)22 Paraná AAB8569 KM897529 ∗
M. piavussu Paranapanema (Canoas)22 Paraná AAB8569 KM897489 ∗
M. piavussu Paranapanema (Canoas)22 Paraná AAB8569 KM897621 ∗
M. piavussu Cinzas (Bandeirantes)25 Paraná AAB8569 KM897419 ∗
M. piavussu Paranapanema (Canoas II)31 Paraná AAB8569 KM897506 ∗
M. piavussu Paranapanema (Canoas II)31 Paraná AAB8569 KM897347 ∗
M. piavussu Paranapanema (Canoas II)31 Paraná AAB8569 KM897192 ∗
M. piavussu Turvo (Icem)21 Paraná AAB8569 KF568991 MZUSP – 113981
M. piavussu Turvo (Icem)21 Paraná AAB8569 KX925486 LISDEBE 6968
M. piavussu Turvo (Icem)21 Paraná AAB8569 KX925487 LISDEBE 6970
M. piavussu Turvo (Icem)21 Paraná AAB8569 KX925488 LISDEBE 6970
M. piavussu Turvo (Icem)21 Paraná AAB8569 KX925489 –
M. piavussu Turvo (Icem)21 Paraná AAB8569 KX925490 –
M. piavussu Turvo (Icem)21 Paraná AAB8569 KX925491 –
M. piavussu Paraná (Porto Camargo)24 Paraná AAB8569 KX925492 –
M. piavussu Paraná (Pauliceia)30 Paraná AAB8569 KX925493 –
M. cf. piavussu lower Paraná Paraná (Rosario)32 Paraná AAB8569 KU288864 ∗
M. cf. piavussu lower Paraná Paraná (Rosario)32 Paraná AAB8569 KU288865 ∗
M. cf. piavussu lower Paraná Paraná (Rosario)32 Paraná AAB8569 KU288866 ∗
M. cf. piavussu lower Paraná Paraná (Rosario)32 Paraná AAB8569 KU289030 ∗
M. reinhardti Pandeiros14 São Francisco AAD1729 HM906025 ∗
M. reinhardti Curimataí17 São Francisco AAD1729 HM405147 MCP – 44776∗
M. reinhardti Curimataí17 São Francisco AAD1729 HM906026 ∗
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 HM906027 ∗
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 HM906028 ∗
M. reinhardti São Francisco (Três Marias)16 São Francisco AAD1729 KX925494 –
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 KX925495 –
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 KX925496 –
M. reinhardti Curimataí17 São Francisco AAD1729 KX925497 MCP - 44770
M. trifasciatus Madeira6 Amazonas ACL3073 KU134864 UFRO-I 4902
M. trifasciatus Ucayali (Pucallpa)5 Amazonas ACL3073 KU134865 MUSM - 47351
M. trifasciatus Ucayali (Pucallpa)5 Amazonas ACL3073 KX925505 MUSM - 47351
M. trifasciatus Amazonas (Belen)3 Amazonas ACL3073 KX925506 MUSM - 47364
M. trifasciatus Lago Catalão (Manaus)4 Amazonas ACL3073 KX925507 INPA 11641
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 HM906028 ∗
M. reinhardti São Francisco (Três Marias)16 São Francisco AAD1729 KX925494 –
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 KX925495 –
M. reinhardti Urucuia (Urucuia)13 São Francisco AAD1729 KX925496 –
M. reinhardti Curimataí17 São Francisco AAD1729 KX925497 MCP - 44770
M. trifasciatus Madeira6 Amazonas ACL3073 KU134864 UFRO-I 4902
M. trifasciatus Ucayali (Pucallpa)5 Amazonas ACL3073 KU134865 MUSM - 47351
M. trifasciatus Ucayali (Pucallpa)5 Amazonas ACL3073 KX925505 MUSM - 47351
M. trifasciatus Amazonas (Belen)3 Amazonas ACL3073 KX925506 MUSM - 47364
M. trifasciatus Lago Catalão (Manaus)4 Amazonas ACL3073 KX925507 INPA 11641
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∗Obtained from BOLD.

DNA Extraction, Amplification, and Sequencing

Total DNA was extracted from tissues (fins, muscle, or liver) by the standard phenol–chloroform method (Sambrook et al., 1989). A fragment of Cytochrome Oxidase subunit I (COI; 698 bp) was amplified via polymerase chain reaction (PCR) using primers AnosCOIF and AnosCOIR (Ramirez and Galetti, 2015). PCR products were sequenced for both strands using an ABI 3730xl (Applied Biosystems, Waltham, MA, United States) automatic sequencer. Contigs were assembled and edited using BioEdit (Hall, 1999). All sequences were evaluated manually, deleting regions of low quality. All sequences were verified to represent the COI gene and were checked for indels and stop codons. GenBank (Benson et al., 2017) accession numbers are given in Table 1. All information about specimen, sequences, and electropherograms were deposited in a data set of The Barcode of Life Database platform (BOLD) with code DS-MGLEP.

DNA Barcode Analysis

The general mixed Yule coalescent (GMYC) model (Pons et al., 2006) with a single threshold, implemented in the splits packages in the R 3.3.3 statistical software (R Core Team, 2017), was used to infer MOTUs. For the GMYC input, an ultrametric tree was generated using Beast 2.4.3 (Bouckaert et al., 2014), with a lognormal relaxed clock, a birth and death model, and a GTR+G substitution model, chosen using jModeltest 2 (Darriba et al., 2012), using 50 million MCMC generations and a burn-in of 10%. Poisson tree processes (PTP) model (Zhang et al., 2013) was used for MOTUs delimitation through the bPTP server1, using default values. The bPTP server includes a Bayesian implementation of the PTP model and the original maximum likelihood PTP. For the PTP input, a tree was generated using Beast 2.4.6 (Bouckaert et al., 2014), with a strict clock, a birth and death model, and the GTR+G substitution model, using 50 million MCMC generations and a burn-in of 10%.

Additionally, two cluster algorithms were used, the Barcode Index Number System (BIN) (Ratnasingham and Hebert, 2013) and Automatic Barcode Gap Discovery (ABGD) (Puillandre et al., 2012). The BIN was automatically determined in the BOLD Workbench, while the ABGD was performed using Kimura-2-parameter (K2P) distance and default values through the web interface2.

COI intraspecific and interspecific genetic distances were estimated using the K2P model implemented in Mega 6.0 (Tamura et al., 2013). These values were used to calculate the mean, minimum, and maximum values for intra- and inter-MOTU distances, and intra- and interspecific distances (nominal species). A genetic distance neighbor-joining (NJ) tree analysis was performed based on the K2P substitution model in Mega 6.0 (Tamura et al., 2013).

Results

The alignment of COI sequences resulted in 600 characters with 158 parsimony informative sites (included in the Supplementary Material). The GMYC analysis resulted in 18 MOTUs (Confidence interval: 16–18) (Table 2). The GMYC model was preferred over the null model (likelihood ratio = 73.49, P < 0.0001), indicating that GMYC results are reliable. The PTP analyses (maximum likelihood and Bayesian implementation) resulted in the same 18 MOTUs obtained in GMYC. The ABGD analysis found six partitions with 27 (P = 0.001) to 16 groups (P = 0.01), including a partition with the same 18 MOTUs (P = 0.005) obtained in the GMYC and PTP analyses. The BOLD system determined 16 BINs (Table 2), showing discordance with our MOTUs in only two BINs, AAB8569 [M. piavussu (Britski et al., 2012) and M. cf. piavussu lower Paraná] and AAD1729 [M. reinhardti (Lütken, 1875) and M. cf. reinhardti]. The clustering of the MOTUs obtained by the analyses is shown in Figure 3.

Table 2.

Genetic K2P distances of Megaleporinus species.

Mean intra- Maximum intra- NN Distance to NN
MOTUs
Megaleporinus brinco 0 0 M. obtusidens 6.78
M. conirostris 0 0 M. cf. conirostris 3.99
M. cf. conirostris 0 0 M. conirostris 3.99
M. elongatus 0.04 0.17 M. cf. obtusidens São Francisco 2.74
M. garmani 0 0 M. obtusidens 7.68
M. macrocephalus 0 0 M. macrocephalus Paraná 1.86
M. macrocephalus Paraná 0 0 M. macrocephalus 1.86
M. muyscorum 0 0 M. reinhardti 11.6
M. cf. muyscorum – – M. trifasciatus 7.48
M. obtusidens 0.14 0.5 M. cf. obtusidens São Francisco 2.84
M. cf. obtusidens Paraguay – – M. piavussu Lower Paranáa 2.9
M. cf. obtusidens São Francisco 0 0 M. elongatus 2.74
M. piavussu 0.06 0.17 M. piavussu Lower Paraná 0.67
M. piavussu Lower Paraná 0.08 0.17 M. piavussu 0.67
M. reinhardti 0 0 M. cf. reinhardti 0.67
M. cf. reinhardti 0 0 M. reinhardti 0.67
M. trifasciatus 0 0 M. macrocephalus 4.52
M. cf. trifasciatus 0 0 M. trifasciatus 6.33
Nominal
Megaleporinus brinco 0 0 M. obtusidens 6.78
M. conirostris 2.13 3.99 M. obtusidens 5.6
M. elongatus 0.04 0.17 M. obtusidens 2.74
M. garmani 0 0 M. obtusidens 7.68
M. macrocephalus 0.86 1.86 M. trifasciatus 4.52
M. muyscorum 7.66 15.31 M. trifasciatus 7.48
M. obtusidens 1.94 6.72 M. elongatus 2.74
M. piavussu 0.26 1.01 M. obtusidens 2.9
M. reinhardti 0.31 0.7 M. conirostris 6.14
M. trifasciatus 3.39 6.33 M. macrocephalus 4.52
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The mean and the maximum of intra-group distances, the nearest neighbor (NN), and the minimum distance to the NN for MOTUs (ABGD, GMYC, and PTP) and Nominal species.

FIGURE 3.

FIGURE 3

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Bayesian tree showing the clustering of the MOTUs obtained by the species delimitation analyses.

Only Megaleporinus brinco (Birindelli and Britski, 2013), Megaleporinus garmani (Borodin, 1929), and Megaleporinus elongatus (Valenciennes, 1850) showed correspondence between nominal species and MOTUs. Within six nominal species, a subdivision in two MOTUs was found, while Megaleporinus obtusidens (Valenciennes, 1837) was divided in three MOTUs (Table 2).

The mean of intra-MOTU and maximum intra-MOTU distances, the nearest neighbor (NN), and the minimum distance to the NN are shown in Table 2, for both GMYC MOTUs and nominal species.

The overall mean of intra-MOTU distances was 0.03%, the maximum intra-MOTU distance was 0.5% (M. obtusidens), and the mean of inter-MOTU distances was 9.19%. The lowest and highest values of inter-MOTU distances were 0.67 and 15.31%, respectively. Considering these values, there is a barcode gap that allowed identifying successfully all MOTUs using COI distance. In contrast, when only the nominal species were considered, the maximum intraspecific distance increased to 15.31% [M. muyscorum (Steindachner, 1900)], and, in addition, no barcode gap was found.

Discussion

Our hypothesis that some of the nominal species represent species complexes separated in different basins could not be rejected by DNA barcoding analysis, revealing taxonomic uncertainties and a hidden diversity within this recently described genus. The DNA barcode analyses identified 16 (ABGD and BIN) to 18 (ABGD, GMYC, and PTP) different MOTUs (Figure 3), with two new MOTUs (M. macrocephalus Paraná and M. cf. piavussu lower Paraná) not analyzed by Ramirez et al. (2017). This high number of MOTUs contrasts with the 10 nominal species recognized in the genus thus far, showing several potential target for cryptic species to be described, reinforcing the general idea that there is still a lot of undocumented diversity within the neotropical ichthyofauna (Reis et al., 2016). The difference between the number of MOTUs detected is due to the lower genetic distance value (0.67%) between two pairs of MOTUs: M. reinhardti and M. cf. reinhardti, separating the genetic lineages from São Francisco and Itapicuru, respectively, and between M. piavussu and M. cf. piavussu lower Paraná. These lower genetic distance values are likely due to a recent divergence between these MOTUs [<0.5 Ma for M. reinhardti and M. cf. reinhardti according to Ramirez et al. (2017)]. Of note, besides presenting an allopatric distribution, these MOTUs were also recovered by the monophyly criterion (Figure 3). MOTUs with recent origin have less time to accumulate genetic differences than species with ancient origin, hindering their identification. Despite this low genetic distance, the species delimitation methods could delimit these MOTUS, especially those based on phylogenetic trees (GMYC and PTP).

A key aspect implicit in the DNA barcoding analysis is the genetic distance threshold used to define MOTUs. COI distances of 1% (Hubert et al., 2008) to 2% (Pereira et al., 2013) have been claimed as threshold to fish DNA barcode analysis. However, such values were derived from comparative analyses among phylogenetically diverse groups. For instance, 2% was used to characterize DNA barcoding of a fish community of a given river (Pereira et al., 2013). However, when the DNA barcoding analyses have focused within a group of species closely related (e.g., a genus), lower threshold values have been reported (Carvalho et al., 2011; Pereira et al., 2011, 2013; Ramirez and Galetti, 2015). Particularly in Anostomidae, a lower threshold of 0.92% was reported to distinguish MOTUs within the genus Laemolyta (Ramirez and Galetti, 2015). Although most of the values obtained herein were above 2% (13 out of 18 MOTUs, Table 2), a maximum threshold of 0.67% for Megaleporinus was detected between the MOTUs obtained. It reinforces that lower genetic distance values might be obtained when intra-genus MOTUs are analyzed, mainly between recent divergent lineages.

Five nominal species, M. conirostris (Steindachner, 1875), M. macrocephalus (Garavello and Britski, 1988), M. muyscorum, M. obtusidens, and M. trifasciatus (Steindachner, 1876), showed high COI distance values (> 1.8%, Table 2) between individuals from different basins, indicating a scenario of potential allopatric speciation within these species.

In contrast to previous results (Avelino et al., 2015), evidence of local differentiation was not found here and all cryptic diversity correspond to inter-basin differentiation. Analyzing only two samples of M. reinhardti from the Três Marias (MG, Brazil) region (São Francisco basin), Avelino et al. (2015) reported an intraspecific distance of 3.8% between them, suggesting a local differentiation. Here we analyzed nine individuals, representing four different localities, including Três Marias region, and we found no genetic distance (0%) among them. Mitochondrial pseudogenes, sequencing errors, or misidentification could explain such discrepancies, and it would be more cautious to consider M. reinhardti from São Francisco as a single MOTU, as recovered here.

Similar discordance is observed for M. piavussu (upper Paraná). Avelino et al. (2015) included four samples from a single locality and reported a mean intraspecific distance of 2.8%. Our present data set for this species included 18 individuals obtained from six localities and showed a lower maximum intraspecific distance of 0.17%. It is strongly suggested that M. piavussu is also a single MOTU.

Incongruences were also observed within the nominal M. obtusidens. While four groups (A–D), showing 0.7–4.1% mean intraspecific distances, were previously reported (Avelino et al., 2015), we found three MOTUs showing 0–0.5% COI distances. The group D mentioned as part of M. obtusidens by Avelino et al. (2015), which included individuals caught downstream the Itaipú dam (Paraná basin), was recovered here as a sister group of M. piavussu, and was named M. cf. piavussu lower Paraná (Figure 3).

One particular aspect was highlighted in our results. Several individuals clustered in the M. macrocephalus clade were caught in different hydrographic basins, as Doce, São Francisco, Tocantins, and Paraná, outside of its original distribution in the Paraguay basin likely due to aquaculture releasing. Similar findings had already been described in the São Francisco basin (Carvalho et al., 2011). This species is a commercial important fish being extensively farmed throughout the Brazilian territory, and accidental or intentional releasing can occur (e.g., Langeani et al., 2007; Vieira, 2010). In such case, the use of DNA barcoding provides a rapid and accurate identification of this species and can be used in management and monitoring potential ecosystem disturbance caused by an invasive species.

In summary, the use of DNA barcoding points at the need for a taxonomic revision of this genus. A search for morphological traits able to support a taxonomic delimitation could be facilitated whether the MOTUs identified here are considered. A morphological trait showing a range of variation when searched within a given nominal species perhaps could be more informative if studied in each MOTU separately. In such case, our results would give an important contribution for the taxonomy of Megaleporinus facilitating the search for decisive taxonomic characters. This is the most complete analysis of DNA barcode in this recently described genus, and considering the economic value of this group, a precise species identification is quite desirable and fundamental for conservation of the whole biodiversity of this genus.

Author Contributions

JR and PG designed the research. JR, DC, PA, PV, HO, MC-A, and JR-P collected data. JR performed the analyses. All authors contributed to the writing of the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We are grateful to C. Cramer, C. Doria, C. Nolorbe, D. Motta, H. Sanchez, J.C. Riofrio, and W. Troy for help to obtain part of the tissue samples and MMA/ICMBIO for collection authorization (32215-1). The authors thank the three reviewers for suggestion and comments which improved the manuscript.

Funding. The authors thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support (Universal 473474/2011-5 and 405309/2016-3 to PG, Universal 420255/2016-8 to JB and Rede BrBOL 564953/2010-5). JR received a fellowship grant from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP 2011/21836-4). Authors received productivity research grants from CNPq (304440/2009-4 to PG) and Fundação Araucária (641/2014 to JB).

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2017.00149/full#supplementary-material

Click here for additional data file. (71.9KB, FASTA)

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