Molecular species delimitation of the genera Anodus, Argonectes, Bivibranchia and Micromischodus (Ostariophysi: Characiformes)

Acácio Freitas Nogueira^1,2,3 , Claudio Oliveira², Francisco Langeani⁴ and Andre Luiz Netto-Ferreira³

PDF: EN    XML: EN  | Cite this article

Abstract​

---

Introduction​

---

South America houses the most diverse freshwater fish fauna on Earth, with about 5,160 spp. (Reis et al., 2016; Dagosta, de Pinna, 2019). However, the taxonomy of this megadiverse ichthyofauna remains unresolved as many species yet wait for description (Birindelli, Sidlauskas, 2018; Albert et al., 2020), whereas other described species contain taxonomic uncertainties, such as species complexes and cryptic biodiversity (Pereira et al., 2013; Guimarães et al., 2018; García-Melo et al., 2019) that hamper proposition of accurate boundaries among closely related species. Indeed, proper species delimitation is a crucial prerequisite to many biological disciplines, such as ecology, population genetics, and conservation, where incorrect identification may lead to a cascade of errors with negative consequences for scientific progress as well as for biodiversity and human welfare (Bortolus, 2008). To circumvent these challenges, DNA information has been used in biodiversity research to take into account the genetic diversity in the identification and discovery of taxa, especially new species (Godfray, 2007).

The first global molecular identification tool proposed for animals was the DNA barcoding, which employs DNA sequences of the mitochondrial gene cytochrome c oxidase I (COI) to create “COI profiles” or barcodes for a particular taxon (Hebert et al., 2003). In the classical framework, such COI profiles are delineated by a particular sequence or a tight cluster of very similar sequences visualized in a Neighbour-joining phenogram constructed under the Kimura 2–parameters model (Hebert et al., 2003; Ward et al., 2005). DNA barcoding successfully delimits species if their representative sequences have intraspecific distance (among them) lower than interspecific distances (among different clusters) (Ratnasingham, Hebert, 2013). For fish and other animals, a fixed threshold of 2% has been proposed to delimitate species (Ward, 2009), however modern use of DNA sequences in alpha taxonomy relies on algorithms for de novo operational taxonomic units (OTU) – picking approaches that cluster sequences into molecular operational taxonomic units (MOTU) or lineages, which may or may not be assigned to morphological species or putative new species (Goldstein, DeSalle, 2011). Some methods are not distance-based, like the DNA barcoding, but theoretically based on the phylogenetic species concept (PSC) and use phylogenetic trees to yield PSC-based results (Zhang et al., 2013).

In the Neotropical freshwater fish fauna, especially within the order Characiformes, molecular sequences, particularly DNA barcoding, have provided a valuable source of information in helping biologists to address many taxonomic questions concerning cryptic biodiversity and species boundaries (Machado et al., 2017; Melo et al., 2018; Arruda et al., 2019; Serrano et al., 2019; Ramirez et al., 2020), and integrative analyses combining molecular and morphological data have been recently used to describe new species (Agudelo-Zamora et al., 2020; Mateussi et al., 2020). However, in some taxa, taxonomic uncertainties persist, especially in groups where the taxonomic delimitation of species has followed the traditional, morphological approach, and has not been scrutinized by molecular tools, and this can be the case of the characiform family Hemiodontidae.

Hemiodontids are swift swimmers with fusiform and streamlined bodies that occur in most rivers and basins of northern South America to the east of the Andes, such as Amazon, Orinoco, Tocantins and Paraná-Paraguay basins, and in rivers of the Guiana Shield and Northeastern Brazil (Langeani, 2003). Most of its members can be distinguished externally from other Characiformes by the possession of a round (midlateral) spot on the flank, an adipose eyelid well-developed covering the entire eye with a narrow opening over the pupil; a suprapectoral sulcus or axillary depression; and nine to 11 branched pelvic-fin rays (Langeani, 1998). Among the five genera in the family, only Hemiodus Müller, 1842 was investigated with molecular data, providing a molecular species delineation for 19 of its 23 valid species based on barcoding (COI gene) sequences (Nogueira et al., 2020). The other four genera, namely Anodus Cuvier, 1829, Argonectes Böhlke & Myers, 1956, Bivibranchia Eigenmann, 1912, and Micromischodus Roberts, 1971 lack molecular studies exploring their species boundaries.

Those four genera lacking molecular studies include ten species (two for Anodus and Argonectes, each, five for Bivibranchia and one for Micromischodus), without any new species being described in the last twenty years (Fricke et al., 2021). These species can be well-distinguished from their congeners by traditional morphological characters (Langeani, 1998). Although the literature seems to indicate little taxonomic problems in these genera (Langeani, 1996), cryptic species, defined as two or more species lacking morphological distinguishability between each other but discernible in other traits such as in genetic, can be hidden even into species without apparent taxonomic problems, as reported for some species of Hemiodus (Nogueira et al., 2020). Therefore, considering the aforementioned lack of molecular taxonomic scrutiny for Anodus, Argonectes, Bivibranchia, and Micromischodus, the aim of the present study is to test the accuracy of morphospecies in those genera via DNA barcoding of automatic species delimitations approaches (ABGD, GMYC, and PTP).

Material and methods

---

Sampling and sequencing. To build our data set, we sequenced the cytochrome c oxidase I (COI) gene for 41 specimens of Anodus, Argonectes, Bivibranchia, and Micromischodus, our focal genera, and downloaded nine other sequences from GenBank (Tab. 1). Downloaded sequences included three from our focal species, four from the related genus Hemiodus and two from other Characiformes families to root the trees (Tab. 1). All voucher specimens sampled in this study are deposited in museum collections. Institutional abbreviations follow Sabaj (2019), except GEPEMA – Grupo de Estudos de Peixes do Médio Araguaia, from UFMT – Universidade Federal de Mato Grosso. Newly generated and downloaded sequences have their GenBank accession numbers at Tab. 1. Vouchers were morphologically identified following original descriptions and taxonomic keys (Langeani, 1996) whenever possible.

Total DNA was extracted from tissue samples preserved in 95% ethanol according to Wizard® Genomic DNA Purification Kit (Promega) manufacturer’s instructions and partial COI sequences were PCR amplified using the primers FishF1 and FishR1 (Ward et al., 2005). PCR reactions were performed in a total volume of 12.5 µl, putting 1.25 µl buffer (10X), 0.5 µl MgCl2 (50 mM), 0.5 µl dNTP (10 mM), 0.25 µl from each primer (200 ng / ml), 0.2 µl Taq DNA polymerase enzyme (5 U / µl), 1 µl DNA (200 ng / µl) and adding double-distillated water to complete final volume. The amplification program consisted of an initial denaturation (94 ºC for 5 min) followed by 25 cycles (94 ºC for 45 s, 54 ºC for 45 s and 68 ºC for 1 min) then a final extension of 68 ºC for 7 min. PCRs products were visualized in 1% agarose gel electrophoresis and after confirmation purified with ExoSap-IT® following the manufacturer’s instructions. Purified PCRs proceeded to sequencing reaction with dye terminator nucleotides (BigDye^TM Terminator v.3.1 Cycle Sequencing Ready Reaction Kit, Applied Biosystems), and the products purified through EDTA + sodium acetate mix and ethanol precipitation. We then sequenced dye-tagged samples in an automatic sequencer ABI 3130-Genetic Analyser (Applied Biosystems®).

Alignment and species delimitation analyses. Forward and reverse strands of each specimen were assembled and edited to form a single consensus sequence in Geneious 8.05 (Kearse et al., 2012). The final matrix of 50 sequences were aligned using the MUSCLE algorithm (Edgar, 2004) in MEGA 7.0 (Kumar et al., 2016) under default parameters and the alignment inspected by eye to detect possible misalignments, like internal gaps. We selected the best-fitting nucleotide substitution model in MEGA 7.0 (Kumar et al., 2016). For the single-locus species delimitation we used three approaches: the Automatic Barcode Gap Discovery – ABGD (Puillandre et al., 2012), the Generalized Mixed Yule Coalescent method – GMYC (Pons et al., 2006; Fujisawa, Barraclough, 2013) and the Poisson Tree Processes model – PTP (Zhang et al., 2013). ABGD was implemented with the MUSCLE aligned matrix as the input file in the ABGD web server (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html) adopting Kimura (k80) model = 2.0, X (relative gap width) = 1.1 and keeping other parameters as default values (Pmin = 0.001, Pmax = 0.1; Steps 10; Nb bins = 20). For the GMYC analysis, an ultrametric tree was generated in BEAST v1.8 (Drummond et al., 2012) running two independent MCMC runs of 40 million generations sampling a tree every 4,000, assuming Birth-Death Process, uncorrelated relaxed lognormal clock model, HKY+G+I model (best model selected) and keeping other parameters as default values. Posterior distributions (ESS > 200) were examined in Tracer v1.6 (Rambaut et al., 2018). The two runs were combined with LogCombiner v1.8.4 (Rambaut, Drummond, 2016a) and then summarized in TreeAnnotator v1.8.4 (Rambaut, Drummond, 2016b) with 25% of the trees discarded as burn-in. GMYC was performed in the package ‘SPLITS’ for R program using the single threshold method. For PTP delimitation, we constructed a maximum likelihood (ML) tree in RAxML v8.2.10 (Stamatakis, 2014) running 20 ML searches to find the best tree with GTR-GAMMA model and keeping other parameters as default values. Topological robustness was verified using bootstrap algorithm (Felsenstein, 1985) through autoMR-based bootstopping criterion, which stops the searching when enough replicates have been achieved. The bootstrap results were reconciled with the best ML tree using draw bipartition. The reconciled draw bipartition tree was used as the input file in the bPTP web server (https://species.h-its.org/ptp) to implement 500,000 MCMC generations (thinning = 500) and keeping other parameters at default values. Additionally, the species in the four genera under analysis that were put together into exclusive cluster or monophyletic group by the phylogenetic analyses used had their intraspecific and interspecific genetic distance calculated and displayed in a pairwise group distance matrix. Genetic distances were calculated in MEGA 7 (Kumar et al., 2016) and corrected by the best model available, keeping other parameters at default settings.

TABLE 1 | Geographic and catalogue museum information of the voucher specimens utilized in this study. *Downloaded from GenBank; **Approximate coordinates.

Results​

---

We obtained partial COI sequences for all valid species into the four analysed genera, resulting in a total of 44 sequences, of which three represent Anodus elongatus Agassiz, 1829; four Anodus orinocensis (Steindachner, 1887); five Argonectes longiceps (Kner, 1858); five Argonectes robertsi Langeani, 1999; six Bivibranchia bimaculata Vari, 1985; six B. fowleri (Steindachner, 1908); three B. notata Vari & Goulding, 1985; two B. simulata Géry, Planquette & Le Bail, 1991; three B. velox (Eigenmann & Myers, 1927); and seven Micromischodus sugillatus Roberts, 1971. Collection sites for the specimens analysed herein are shown in Fig. 1. The alignment of 50 COI sequences (ingroup plus outgroups) yielded a total of 650 positions in the final matrix with 228 variable sites and 203 parsimony informative sites. Nucleotide frequency was 23.3% adenine, 28.4% cytosine, 18.5% guanine and 29.8% thymine. Average values of intra- and interspecific genetic distance for the ten species analysed are shown in Tab. 2. Genetic distances were calculated by the Tamura Nei (TN93) model, the second best ranked because HKY is not available for computing genetic distance in MEGA. Average intraspecific genetic distance (bold number) ranged from 0.001 within Bivibranchia bimaculata, B. notata, B. velox and Micromischodus sugillatus to 0.039 within B. fowleri. For interspecific distance, the lowest average value was 0.055 between the two species of Argonectes and the highest was 0.215 between Bivibranchia fowleri and Micromischodus sugillatus.

FIGURE 1 | Map of northern South America showing collection sites of Hemiodontidae specimens analysed in this study, per species.

TABLE 2 | Matrix of pairwise TN93 genetic distance among species of Hemiodontidae with interspecific distances below the diagonal of bold numbers, the standard error estimates of interspecific distances above this diagonal and bold numbers representing intraspecific genetic distance.

In the molecular delimitation analyses, the maximum clade credibility tree generated by the Bayesian inference was used to display the results in Fig. 2. The ABGD method resulted in nine partitions ranging from 9 to 18 groups or MOTUs for the ten species. The most frequent result was the number of 12 MOTUs, found in three partitions (Pmax range = 0.0046 to 0.0129). This result is also realistic and conservative considering the total number of valid species. The maximum likelihood (ML) result of GMYC delimited 14 ML entities that are all delimited lineages including single specimen MOTUs. The likelihood of the GMYC model (= 299.9232) is higher than the likelihood of the null model (= 267.2621), indicating that GMYC results are reliable. The ML solution of the PTP delineated 14 MOTUs. All delimitation results described above do not include the outgroups.

FIGURE 2 | Bayesian tree of the specimens showing the MOTUs delimited by ABGD, PTP, and GMYC methods. Congruence across methods is represented by black rectangles and discordance between them is represented by grey rectangles.

GMYC and PTP defined the same MOTUs, meaning total congruence between both tree-based methods, indeed the trees used as inputs for these methods, which are ML and Bayesian trees, are very similar in topology. Species matched by just one MOTU in all delimitation strategies were Anodus elongatus, Argonectes longiceps, Argonectes robertsi, Bivibranchia bimaculata, B. notata, B. velox, and Micromischodus sugillatus. About divergence across methods, only ABGD established one MOTU for Anodus orinocensis whereas PTP and GMYC defined the sole specimen from the Orinoco River (LBP 15615), the type locality of the species, as one MOTU and the other three specimens, coming from the Amazon (INPA) and Araguaia-Tocantins (GEPEMA) basins, as another MOTU. The two samples of Bivibranchia simulata constituted a single MOTU in the ABGD results but were divided in two by the tree-based methods, constituting two single specimen MOTUs, distributed into two geographically close but independent water bodies, the Brokopondo and Nickerie Rivers.

Discussion​

---

As all delimitation approaches showed absolutely concordance in delimiting Anodus elongatus, Argonectes longiceps, Argonectes robertsi, Bivibranchia bimaculata, B. notata, B. velox, and Micromischodus sugillatus, with total correspondence between nominal species and MOTUs, these delimitation results should probably be correct (Dellicour, Flot, 2018). The conservativeness of the AGBD and the similarity between GMYC and PTP obtained herein were also observed in the species delimitation of other characiform fishes, like in the subfamily Stevardiinae (genera Bryconamericus Eigenmann, 1907, Hemibrycon Günther, 1864, Knodus Eigenmann, 1911, and Eretmobrycon Fink, 1976), where ABGD yields a more conservative delimitation, close to the number of morphological species, while GMYC and PTP yield more splits and similar number of MOTUs (García-Melo et al., 2019); and in the genus Megaleporinus Ramirez, Birindelli & Galetti, 2017, where the same 18 MOTUs were obtained by GMYC and PTP, whereas ABGD recovered, in six partitions, from 16 to 27 MOTUs (Ramirez et al., 2017). On the other hand, is noteworthy that the three individuals of Bivibranchia notata, a species occurring in the rivers Tapajós, Trombetas and Tocantins, from an unique place in the Teles Pires River (a Tapajós tributary) could cause biases in the delimitation process since intraspecific genetic variation tends to increase with increases in geographical scale (Bergsten et al., 2012), but congruence among results across different strategies are good indicative that main assumptions of them were not violated, reducing the potential bias of the present result (Carstens et al., 2013). A similar situation of limited geographical sampling is the case of Bivibranchia velox, which occurs in the Xingu and Araguaia-Tocantins basins, but was sampled only in the Araguaia River.

The four samples of Anodus orinocensis were scattered over a huge area in South America with collection sites spanning large distances from each other but encompassing the three basins in which the species occurs, Amazon, Orinoco and Araguaia-Tocantins (see Fig. 1). This sparse geographical sampling can negatively impact the effectiveness of the delimitation methods because intermediated populations may not be considered, violating the assumption that geographic sampling is comprehensive with most or all populations, biogeographic regions, and contact zones being represented (Mason et al., 2020). Violated assumptions may lead to errors in delimitation outcomes that we can notice in discordant results across different delimitation methods (Carstens et al., 2013). The prominent type of error in ABGD is overlumping, whereas the main type of error in tree-based approaches is oversplitting (Dellicour, Flot, 2018). Those arguments seem to meet what we found in Anodus orinocensis with possible overlumping in ABGD or oversplitting in GMYC and PTP. In such cases of uncertainties, a conservative inference is preferable, for in most context it is better to fail to delimit species than to falsely delimit entities that do not represent true independent lineages (Carstens et al., 2013). Therefore we suggest Anodus orinocensis having two structured populations, as GMYC has been criticized for assuming that species comprise a single unstructured population and can mistakenly delimit isolated population as separate species, especially if linking populations have not been sampled (Fujisawa, Barraclough, 2013).

Bivibranchia fowleri was the most split species with three MOTUs delimited in all outcomes. Its sampling scenario encompasses most of its geographical distribution (see Langeani, 2003) with representatives lacking only from the Tocantins and Madeira Rivers. Broad sampling is especially good for widespread species, like Bivibranchia fowleri, because it would maximize the chance of including intermediate (population) diversity and thus generating more accurate results (Mason et al., 2020). Also, species sampled throughout its geographical range will reveal greater genetic variation than if the variation was estimated from a single smaller region (Bergsten et al., 2012), which can explain the greatest intraspecific genetic distance found in Bivibranchia fowleri, 3.9%, probably because more linking populations were sampled. After checked the vouchers, we did not find morphological differences that justify the description of new species, and we propose that Bivibranchia fowleri may contain cryptic species, regarding COI sequences, or structured population, similar to what was proposed for Pygocentrus nattereri Kner, 1858 (Mateussi et al., 2019). Such cryptic speciation may have evolved by recent divergence in which cryptic species are sister taxa or members of a species complex with short divergence times and morphological traits evolving slowly under neutral evolution or might be constrained by stabilizing selection and represent early stages of morphological stasis (Fišer et al., 2018; Struck et al., 2018).

Bivibranchia simulata is the least sampling taxon or the rarest species with only two individuals sampled, but it is among the hemiodontids with one of the smallest distribution range (Langeani, 2003) and DNA barcoding delimit more accurately species with smaller geographical scale (Bergsten et al., 2012). Unfortunately this scenario for Bivibranchia simulata is the reality of many DNA studies in biodiversity where rarity and small geographical ranges for many species are due to logistics of fieldwork (Ahrens et al., 2016). Comparing the delineation strategies, ABGD is known for performing slightly worse than tree-based methods on simulated data sets using a sampling scheme with a few abundant species and many rare ones (Dellicour, Flot, 2018), the case found here for Bivibranchia simulata. Indeed, rarely sampled species are not problematic per se for GMYC and PTP approaches (Ahrens et al., 2016; Dellicour, Flot, 2018). A solution to compensate or overcome the limitations of low sample size (rare species and singletons) is adding closely related species or clades (“clade-wise addition”) to the rare taxon (Ahrens et al., 2016), and Bivibranchia simulata meets this solution because it is surrounded by all their closely related clades, that are all other valid species within Bivibranchia. Nevertheless, in face of the conflicting results and low sampling we tend to the conservative way, likewise that for Anodus orinocensis, and propose that the two single specimen MOTUs delimited in Bivibranchia simulata by the tree-based approaches most likely constitute genetically-structured lineages like has been proposed in the characiforms genera Brycon Müller & Troschel, 1844 (Arruda et al., 2019) and Pygocentrus Müller & Troschel, 1844 (Mateussi et al., 2019). It is worthy to mention that Géry et al. (1991) have already noticed morphological variation among some other subsets of B. simulata populations, which were described by them as distinct subspecies: B. s. simulata from French Guyana, in the Oyapoque River, and B. s. surinamensis from Suriname, in the Coppename, Nickerie, and Suriname Rivers. These two subspecies were later considered synonyms by Langeani (2003), taking the same conservative decision as ours here.

Unlike the results of Nogueira et al. (2020) that strongly suggested cryptic and undescribed species for Hemiodus, the three species herein that matched more than one MOTUs per nominal species did not have congruent results across all methods and most probably be cases of recent divergence in which MOTUs are exhibiting different degrees of genetic divergence, but not high enough to be detected by all methods. Nevertheless, those MOTUs hidden into the three taxa could be better highlighted by using other data sets and analyses, maybe multi-locus analyses (Piggott et al., 2011), or by adding more individuals from distant localities (Mason et al., 2020). Despite those limitations, the present survey is the broadest molecular study ever done for Hemiodontidae including all valid species in the focal genera without any singleton (i.e., MOTUs represented by just one individual) while the study of Nogueira et al. (2020) did not include all valid Hemiodus species and three species were represented by singletons. Also, the results obtained here reveal a broad and strong congruence between current valid species and MOTUs, with seven of ten species being matched by exactly one MOTU, equally delimited by all strategies. This correspondence of 70% between nominal species and mitochondrial lineages may highlight a relatively stable taxonomy for these four genera of Hemiodontidae.

Acknowledgments​

---

We are grateful to the following researchers and institutions for donations of tissue samples: Mark Sabaj and Mariangeles Arce from ANSP Fish Collection (iXingu Project & NSF DEB–1257813); Érica Caramaschi and Bruno Eleres from DEPRJ (UFRJ); Camila Ribas from INPA (Avian Collection); Carlos Lucena from MCP (PUC-RS); José Birindelli from MZUEL; Aléssio Datovo and Osvaldo Oyakawa from MZUSP; Raphael Covain from MHNG; Mary Burridge and Erling Holm from ROM-Ichthyology. We also thank UNESP to provide tissue samples (LBP) and Brycon server (LBP-IBB; FAPESP proc. 2014/26508.3) where were executed the phylogenetic analyses. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES) – finance code 001 (Acácio Nogueira). Francisco Langeani receives financial support by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, proc. 305756/2018–4). Claudio Oliveira receives financial support from Fundação de Amparo à Pesquisa do Estado de São Paulo – FAPESP grants 2018/20610-1, 2016/09204–6, 2014/26508–3 and Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq proc. 306054/2006–0.

References​

---

Agudelo-Zamora HD, Tavera J, Murillo YD, Ortega-Lara A. The unknown diversity of the genus Characidium (Characiformes: Crenuchidae) in the Chocó biogeographic region, Colombian Andes: Two new species supported by morphological and molecular data. J Fish Biol. 2020; 97(6):1662–75. doi: https://doi.org/10.1111/jfb.14527.

Ahrens D, Fujisawa T, Krammer HJ, Eberle J, Fabrizi S, Vogler AP. Rarity and incomplete sampling in DNA-based species delimitation. Syst Biol. 2016; 65(3):478–94. doi: https://doi.org/10.1093/sysbio/syw002.

Albert JS, Tagliacollo VA, Dagosta F. Diversification of Neotropical freshwater fishes. Annu Rev Ecol Evol Syst. 2020; 51(1). doi: https://doi.org/10.1146/annurev-ecolsys-011620-031032.

Arruda PSS, Ferreira DC, Oliveira C, Venere PC. DNA barcoding reveals high levels of divergence among mitochondrial lineages of Brycon (Characiformes, Bryconidae). Genes (Basel). 2019; 10(9):5–07. doi: https://doi.org/10.3390/genes10090639.

Bergsten J, Bilton DT, Fujisawa T, Elliott M, Monaghan MT, Balke M et al. The effect of geographical scale of sampling on DNA barcoding. Syst Biol. 2012; 61(5):851–69. doi: https://doi.org/10.1093/sysbio/sys037.

Birindelli JLO, Sidlauskas BL. Preface: How far has Neotropical Ichthyology progressed in twenty years? Neotrop Ichthyol. 2018; 16(3):1–8. doi: https://doi.org/10.1590/1982-0224-20180128.

Bonani Mateussi NT, Melo BF, Oliveira C. Molecular delimitation and taxonomic revision of the wimple piranha Catoprion (Characiformes: Serrasalmidae) with the description of a new species. J Fish Biol. 2020; 97(3):668–85. doi: https://doi.org/10.1111/jfb.14417.

Bortolus A. Error cascades in the biological sciences: The unwanted consequences of using bad taxonomy in ecology. Ambio. 2008; 37(2):114–18. doi: https://doi.org/10.1579/0044-7447(2008)37[114:ECITBS]2.0.CO;2.

Carstens BC, Pelletier TA, Reid NM, Satler JD. How to fail at species delimitation. Mol Ecol. 2013; 22(17):4369–83. doi: https://doi.org/10.1111/mec.12413.

Dagosta FCP, de Pinna M. The fishes of the Amazon: distribution and biogeographical patterns, with a comprehensive list of species. Bull Am Museum Nat Hist. 2019(431):1–163.

Dellicour S, Flot JF. The hitchhiker’s guide to single-locus species delimitation. Mol Ecol Resour. 2018; 18(6):1234–46. doi: https://doi.org/10.1111/1755-0998.12908.

Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian Phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012; 29(8):1969–73. doi: https://doi.org/10.1093/molbev/mss075.

Edgar RC. MUSCLE: A multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004; 5:1–19. doi: https://doi.org/10.1186/1471-2105-5-113.

Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evoltution. 1985; 39:783–91.

Fišer C, Robinson CT, Malard F. Cryptic species as a window into the paradigm shift of the species concept. Mol Ecol. 2018; 27(3):613–35. doi: https://doi.org/10.1111/mec.14486.

Fricke R, Eschmeyer WN, van der Laan R. Eschmeyer’s catalog of fishes: genera, species, references 2021. http://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp (accessed January 2, 2021).

Fujisawa T, Barraclough TG. Delimiting species using single-locus data and the generalized mixed Yule coalescent approach: a revised method and evaluation on simulated data sets. Syst Biol. 2013; 62(5):707–24. doi: https://doi.org/10.1093/sysbio/syt033.

García-Melo JE, Oliveira C, Da Costa Silva GJ, Ochoa-Orrego LE, Garcia Pereira LH, Maldonado-Ocampo JA. Species delimitation of Neotropical Characins (Stevardiinae): Implications for taxonomy of complex groups. PLoS One. 2019; 14(6):1–22. doi: https://doi.org/10.1371/journal.pone.0216786.

Géry J, Planquette P, Le Bail PY. Faune characoïde (poissons ostariophysaires) de l’Oyapock, l’Approuague et la rivière de Kaw (Guyane Française). Cybium. 1991: 15(1): 1-69.

Godfray HCJ. Linnaeus in the information age. Nature. 2007; 446(7133):259–60. doi: https://doi.org/10.1038/446259a.

Goldstein PZ, DeSalle R. Integrating DNA barcode data and taxonomic practice: Determination, discovery, and description. BioEssays. 2011; 33(2):135–47. doi: https://doi.org/10.1002/bies.201000036.

Guimarães KLA, de Sousa MPA, Ribeiro FRV, Porto JIR, Rodrigues LRR. DNA barcoding of fish fauna from low order streams of Tapajós River basin. PLoS One. 2018; 13(12):1–16. doi: https://doi.org/10.1371/journal.pone.0209430.

Hebert PDN, Cywinska A, Ball SL, DeWaard JR. Biological identifications through DNA barcodes. Proc R Soc B Biol Sci. 2003; 270(1512):313–21. doi: https://doi.org/10.1098/rspb.2002.2218.

Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 2012; 28(12):1647–49. doi: https://doi.org/10.1093/bioinformatics/bts199.

Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for bigger datasets. Mol Biol Evol. 2016; 33(7):1870–74. doi: https://doi.org/10.1093/molbev/msw054.

Langeani F. Family Hemiodontidae. In: Reis RE, Kullander SO, Ferraris CJ, editors. Check List Freshw. Fishes South Cent. Am. Porto Alegre: Edipucrs; 2003. p.742.

Langeani F. Phylogenetic study of the Hemiodontidae (Ostariophysi: Characiformes). In: Malabarba LR, Reis RE, Vari RP, Lucena ZM, Lucena C, editors. Phylogeny Classif. Neotrop. Fishes. Porto Alegre: Edipucrs; 1998. p.145–60.

Langeani F. Estudo filogenético e revisão taxonômica da família Hemiodontidae Boulenger, 1904 (sensu Roberts, 1974) (Ostariophysi, Characiformes). [PhD Thesis]. São Paulo: Universidade de São Paulo; 1996.

Machado CB, Ishizuka TK, Freitas PD, Valiati VH, Galetti PM. DNA barcoding reveals taxonomic uncertainty in Salminus (Characiformes). Syst Biodivers. 2017; 15(4):372–82. doi: https://doi.org/10.1080/14772000.2016.1254390.

Mason NA, Fletcher NK, Gill BA, Funk WC, Zamudio KR. Coalescent-based species delimitation is sensitive to geographic sampling and isolation by distance. Syst Biodivers. 2020; 18(3):269–80. doi: https://doi.org/10.1080/14772000.2020.1730475.

Mateussi NTB, Melo BF, Foresti F, Oliveira C. Molecular data reveal multiple lineages in piranhas of the genus Pygocentrus (Teleostei, Characiformes). Genes (Basel). 2019; 10(5):371. doi: https://doi.org/10.3390/genes10050371.

Melo BF, Dorini BF, Foresti F, Oliveira C. Little divergence among mitochondrial lineages of Prochilodus (Teleostei, Characiformes). Front Genet. 2018; 9(APR):1–09. doi: https://doi.org/10.3389/fgene.2018.00107.

Nogueira AF, Oliveira C, Langeani F, Netto-Ferreira AL. Overlooked biodiversity of mitochondrial lineages in Hemiodus (Ostariophysi, Characiformes). Zool Scr. 2020(December):1–15. doi: https://doi.org/10.1111/zsc.12469.

Pereira LHG, Hanner R, Foresti F, Oliveira C. Can DNA barcoding accurately discriminate megadiverse Neotropical freshwater fish fauna? BMC Genet. 2013; 14(1):20. doi: https://doi.org/10.1186/1471-2156-14-20.

Piggott MP, Chao NL, Beheregaray LB. Three fishes in one: Cryptic species in an Amazonian floodplain forest specialist. Biol J Linn Soc. 2011; 102(2):391–403. doi: https://doi.org/10.1111/j.1095-8312.2010.01571.x.

Pons J, Barraclough TG, Gomez-Zurita J, Cardoso A, Duran DP, Hazell S et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst Biol. 2006; 55(4):595–609. doi: https://doi.org/10.1080/10635150600852011.

Puillandre N, Lambert A, Brouillet S, Achaz G. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol Ecol. 2012; 21:1864–77. doi: https://doi.org/10.1111/j.1365-294X.2011.05239.x.

Rambaut A, Drummond AJ. LogCombiner v1.8.4 2016a.

Rambaut A, Drummond AJ. TreeAnnotator v1.8.4 2016b.

Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior summarization in Bayesian hylogenetics using Tracer 1.7. Syst Biol. 2018; 67(5):901–4. doi: https://doi.org/10.1093/sysbio/syy032.

Ramirez JL, Birindelli JL, Carvalho DC, Affonso PRAM, Venere PC, Ortega H et al. Revealing hidden diversity of the underestimated neotropical ichthyofauna: DNA barcoding in the recently described genus Megaleporinus (Characiformes: Anostomidae). Front Genet. 2017; 8(OCT):1–11. doi: https://doi.org/10.3389/fgene.2017.00149.

Ramirez JL, Santos CA, Machado CB, Oliveira AK, Garavello JC, Britski HA et al. Molecular phylogeny and species delimitation of the genus Schizodon (Characiformes, Anostomidae). Mol Phylogenet Evol. 2020; 153(August):106959. doi: https://doi.org/10.1016/j.ympev.2020.106959.

Ratnasingham S, Hebert PDN. A DNA-based registry for all animal species: The Barcode Index Number (BIN) System. PLoS One. 2013; 8(7). doi: https://doi.org/10.1371/journal.pone.0066213.

Reis R, Albert J, Di Dario F, Mincarone M, Petry P, Rocha L. Fish biodiversity and conservation in South America. J Fish Biol. 2016; 89(1):12–47. doi: https://doi.org/10.1111/jfb.13016.

Serrano ÉA, Melo BF, Freitas-Souza D, Oliveira MLM, Utsunomia R, Oliveira C et al. Species delimitation in Neotropical fishes of the genus Characidium (Teleostei, Characiformes). Zool Scr. 2019; 48(1):69–80. doi: https://doi.org/10.1111/zsc.12318.

Stamatakis A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014; 30(9):1312–13. doi: https://doi.org/10.1093/bioinformatics/btu033.

Struck TH, Feder JL, Bendiksby M, Birkeland S, Cerca J, Gusarov VI et al. Finding evolutionary processes hidden in ryptic species. Trends Ecol Evol. 2018; 33(3):153–63. doi: https://doi.org/10.1016/j.tree.2017.11.007.

Ward RD. DNA barcode divergence among species and genera of birds and fishes. Mol Ecol Resour. 2009; 9(4):1077–85. doi: https://doi.org/10.1111/j.1755-0998.2009.02541.x.

Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN. DNA barcoding Australia’s fish species. Philos Trans R Soc B Biol Sci. 2005; 360(1462):1847–57. doi: https://doi.org/10.1098/rstb.2005.1716.

Zhang J, Kapli P, Pavlidis P, Stamatakis A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics. 2013; 29(22):2869–76. doi: https://doi.org/10.1093/bioinformatics/btt499.

Authors

---

Acácio Freitas Nogueira^1,2,3 , Claudio Oliveira², Francisco Langeani⁴ and Andre Luiz Netto-Ferreira³

^[1]    Programa de Pós-Graduação em Zoologia, Instituto de Ciências Biológicas, Universidade Federal do Pará and Museu Paraense Emílio Goeldi, Rua Augusto Corrêa, 01, 66075-110 Belém, PA, Brazil. (AFN) acacio.freitas89@gmail.com (corresponding author).

^[2]    Laboratório de Biologia e Genética de Peixes, Departamento de Biologia Estrutural e Funcional, Instituto de Biociências, Universidade Estadual Paulista, Rua Prof. Dr. Antônio C. W. Zanin, 250, 18618-689 Botucatu, SP, Brazil. (CO) claudio.oliveira@unesp.br.

^[3]    Laboratório de Ictiologia, Departamento de Zoologia, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, 91501-970 Porto Alegre, RS, Brazil. (ALNF) alnferreira@gmail.com.

^[4]    Departamento de Ciências Biológicas, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista, Rua Cristóvão Colombo, 2265, 15054-000 São José do Rio Preto, SP, Brazil. (FL) francisco.langeani@unesp.br.

Authors Contribution

---

Acácio Freitas Nogueira: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft.

Claudio Oliveira: Conceptualization, Funding acquisition, Project administration, Resources, Supervision.

Francisco Langeani: Conceptualization, Project administration, Supervision, Visualization, Writing-original draft.

Andre Luiz Netto-Ferreira: Conceptualization, Investigation, Project administration, Resources, Supervision, Validation, Writing-original draft.

Ethical Statement​

---

Not applicable.

Competing Interests

---

The authors declare no competing interests.

How to cite this article

---

Nogueira AF, Oliveira C, Langeani F, Netto-Ferreira AL. Molecular species delimitation of the genera Anodus, Argonectes, Bivibranchia and Micromischodus (Ostariophysi: Characiformes). Neotrop Ichthyol. 2021; 19(4):e210005. https://doi.org/10.1590/1982-0224-2021-0005

Copyright​

---

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Distributed under

Creative Commons CC-BY 4.0

© 2021 The Authors.

Diversity and Distributions Published by SBI

Accepted October 15, 2021 by Alexandre Hilsdorf

Submitted January 5, 2021

Epub December 13, 2021