Journal of Fish Biology (2015) doi:10.1111/jfb.12707, available online at wileyonlinelibrary.com DNA barcoding and morphological identification of neotropical ichthyoplankton from the Upper Paraná and São Francisco R. A. Becker, N. G. Sales, G. M. Santos, G. B. Santos and D. C. Carvalho* Pontifícia Universidade Católica de Minas Gerais, Programa de Pós-graduação em Zoologia de Vertebrados, Laboratório de Genética da Conservação, Rua Dom José Gaspar, 500, 30535-901 Belo Horizonte, MG, Brazil (Received 6 October 2014, Accepted 1 April 2015) The identification of fish larvae from two neotropical hydrographic basins using traditional morphological taxonomy and DNA barcoding revealed no conflicting results between the morphological and barcode identification of larvae. A lower rate (25%) of correct morphological identification of eggs as belonging to migratory or non-migratory species was achieved. Accurate identification of ichthyoplankton by DNA barcoding is an important tool for fish reproductive behaviour studies, correct estimation of biodiversity by detecting eggs from rare species, as well as defining environmental and management strategies for fish conservation in the neotropics. 2015 The Fisheries Society of the British Isles Key words: biodiversity; eggs; fishes; fresh water; larvae; molecular taxonomy. INTRODUCTION Unambiguous identification of fish eggs and larvae is an important tool for fish ecology and conservation. For instance, it may allow the detection of spawning areas, the monitoring of fish stocks affected by dams and improve fisheries management and conservation policies (Baumgartner et al., 2004; Reynalte-Tataje et al., 2004; Agostinho et al., 2007; Moura et al., 2008; Valdez-Moreno et al., 2010). The ontogenetic morphological variation of larvae and the extreme biological diversity of neotropical ichthyofauna (around 3500 described species) (Reis et al., 2003) means that studies related to egg and larva identification are restricted to a few well-studied areas (Nakatani et al., 2001). As a consequence of these issues, the neotropical region has the lowest number of studies related to ichthyoplankton identification, despite its species diversity (Oliveira et al., 2008; Hermes-Silva et al., 2009). Moreover, all published work to date regarding egg and larval identification has been based solely on morphological characteristics and rarely reached identification to the species level (Nakatani et al., 2001; Graça & Pavanelli, 2007). In some cases, the studies analysed only abundance of ichthyoplankton, avoiding any tentative taxonomic identification of larvae (Gogola et al., 2010). *Author to whom correspondence should be addressed. Tel.: +55 (31) 3319 4967; email: danielcarvalho @pucminas.br 1 2015 The Fisheries Society of the British Isles
2 R. A. BECKER ET AL. Therefore, a major obstacle for a broader use of fish larvae and egg surveys is their unambiguous identification (Gleason & Burton, 2012). For instance, Ko et al. (2013) morphologically identified larvae from the Taiwan coast and reported that only 13 5% were identified to the species level and 43% could not be identified due to the lack of diagnostic morphological traits. On the other hand, using a DNA-based technique (i.e. DNA barcoding), 69% of all larvae were identified to the species level (Ko et al., 2013). Reported morphological difficulties are normally due to shared morphological features and intraspecific morphological variation (Bialetzki et al., 1998, 2001, 2008). Additionally, it is only possible to differentiate fish eggs as belonging to migratory or non-migratory species as the perivitellinic space is the only diagnostic characteristic available (Nakatani et al., 2001; Leite et al., 2007; Oliveira & Ferreira, 2008). A broad range of molecular tools has been used to improve ichthyoplankton identification accuracy, including species-specific fluorescent-labelled probes (Gleason & Burton, 2012) to a high-throughput robotic sample handling process (Richardson et al., 2007). Most studies make use of developed libraries for species identification through DNA barcoding (650 bp of the mitochondrial gene coi), a technique which allows the identification of samples lacking diagnostic morphological characteristics, such as processed fish products (e.g. fish fillets and caviar), stomach contents as well as fish larvae and eggs (Desalle & Amato, 2004; Carreon-Martinez et al., 2011; Carvalho et al., 2011a; Ko et al., 2013; Arroyave & Stiassny, 2014; Loh et al., 2014). For instance, Loh et al. (2014) developed and applied DNA barcoding to identify 14 of the 16 species inhabiting the Brisbane River (Australia), including a quantitative (q)pcr assay for species-specific detection and quantification. For marine fish species, results using DNA barcoding have shown a high error rate of morphological identification to the species level of eggs and larvae (Ahlstrom & Moser, 1976; Shao et al., 2002). When considering Brazilian biodiversity, with over 2587 known species representing around 25% of the described freshwater fish species (Buckup et al., 2007), however, the accuracy of morphological identification of ichthyoplankton has not yet been investigated. In order to investigate the gain achieved by integrating DNA barcoding and neotropical ichthyoplankton taxonomy, the accuracy of the morphological identification of larvae conducted by two independent laboratories was investigated and compared with identification provided by DNA barcodes. Secondly, the efficiency of morphological diagnostic feature for egg identification (i.e. perivitellinic space) was evaluated in differentiating migratory from non-migratory freshwater fish species. SAMPLING MATERIALS AND METHODS Ichthyoplankton samples were obtained from Nova Ponte reservoir, located on the Araguari River (upper Paraná River basin; 19 19 3 57 S; 46 49 23 26 W) and the Pará River (São Francisco Basin; 19 45 46 10 S; 44 53 57 58 W), south-eastern Brazil. The São Francisco River and the upper Paraná River Basin encompass the most urbanized and exploited area of Brazil, representing two major South American basins. Inventories of their freshwater fish fauna found at least 205 and 310 valid species in each of the rivers, respectively; however, many putative species are yet to be described (Alves et al., 2007; Langeaniet al., 2007). DNA barcode
DNA BARCODING OF NEOTROPICAL ICHTHYOPLANKTON 3 libraries have already been developed for most species from both fish faunas (Carvalho et al., 2011b; Pereira et al., 2013). A 500 μm conic net 1 45 m long and 38 cm in diameter was used for sampling. All ichthyoplankton samples were fixed in ethanol (100%) and measured (total length, L T ) using a stereoscopic microscope with a micrometre ruler coupled to the ocular lens. Before extracting DNA, the same larvae were morphologically identified by two independent research laboratories. As all eggs and larvae were macerated for DNA extraction, photographs were taken and kept as vouchers. Larvae and fish eggs are classified as zooplankton; therefore, no permit is needed for their collection in Brazil and no specific permission was required for collecting zooplankton from the sample sites. MORPHOLOGICAL IDENTIFICATION Eggs were identified as belonging to migratory species (eggs with a large perivitellinic space) and non-migratory (reduced perivitellinic space) (Nakatani et al., 2001; Leite et al., 2007; Oliveira & Ferreira, 2008) according to Agostinho et al. (2003). Larvae were identified to the lowest possible taxonomic level by two separate laboratories: the Conservation Genetics Laboratory at the Pontifícia Universidade Católica de Minas Gerais (Laboratory LGC-PUC), Brazil and the Ichthyoplankton Laboratory from the Núcleo de Pesquisas em Limnologia e Aquicultura (Laboratory NUPELIA), State University of Maringá, Brazil. The larvae s embryonic development was defined according to its ontogenetic development: larval yolk sac, preflexion, flexion and postflexion according to morphological traits suggested by Ahlstrom & Moser (1976) and Nakatani et al. (2001). Larvae belonging to the order Characiformes were identified by the absence of barbels, dermic plates, protractile mouth and the presence of an anal opening in the middle of the body. The order Gymnotiformes were characterized by the presence of the anal opening located on the anterior half of the body, a falciform-shaped body and the absence of a caudal fin. The order Siluriformes was differentiated by the presence of barbels. The Anostomidae has two small chromatophores on the frontal head region, and the family Characidae was identified by excluding the other characteristics that define other families from the Characiformes order. The family Poecilidae has highly developedeyesand a rounded caudalfin (Nakataniet al., 2001; Graça & Pavanelli, 2007). DNA BARCODING DNA was extracted using a modified salting-out protocol (Sunnucks & Hales, 1996) or commercial kits (Nucleo Spin kit and Nucleo Spin XS kit; Macherey-Nagel; www.mn-net.com), following the manufacturer s instructions. Before DNA extraction, eggs and larvae were washed in ultrapure water and then macerated. Partial cytochrome c oxidase I (coi) gene sequences of c. 650 bp were amplified by PCR using primers FishF1 and FishR1 (Ward et al., 2009). PCR consisted of 1 0 μl of buffer, 0 2 μl of deoxynucleotide triphosphate (dntp) (10 mm), 0 3 μl of MgCl 2,0 2 μl of each primer (10 μm), 0 1 μl of Taq polymerase, 7 0 μl of ultrapure water and 1 0 μl of genomic DNA. PCR conditions comprised an initial step of 2 min at 95 Cfollowed by 35 cycles of 30 s at 95 C, 30 s at 54 C and 60 s at 72 C, and one final step of 10 min at 72 C. PCR products were visualized in 1% agarose gel, and successfully amplified samples were selected for sequencing. DNA sequencing was conducted in both directions, and sequences were obtained using an automated DNA sequencing device 3500 (Life technologies; www.lifetechnologies.com). DATA ANALYSIS The consensus DNA sequence was obtained, checked visually using the DNA Baser software (www.dnabaser.com) and ambiguous ends were removed. All sequences were compared with the existing Barcode of Life Data (BOLD; www.boldsystems.org) and GenBank (www.ncbi.nlm.nih.gov/genbank) databases for sample identification using the BOLD Identification tool and basic local-alignment search tool (BLAST), respectively. DNA sequences, images and geographic location of all ichthyoplankton were deposited in BOLD under accession numbers LARVA00114 LARVA09714.
4 R. A. BECKER ET AL. (a) (b) (c) (d) (e) (f) Morphology Migratory Migratory? Non-migratory Non-migratory Non-migratory DNA barcode P. maculatus (M) P. maculatus (M) P. maculatus (M) L. octofasciatus (N-M) L. octofasciatus (N-M) P. maculatus (M) Fig. 1. Morphological and DNA barcode identification of neotropical fish eggs. (a, b), Eggs were identified as migratory fish species due to the reduced perivitellinic space. (d, e, f) Eggs presenting developed perivitellinic space were classified as non-migratory species. The visualization of perivitellinic space of egg (c) was hampered due to the presence of collated organic matter. Eggs identified through DNA barcoding as migratory species Pimelodus maculatus (a, b, c, f) varied widely in their perivitellinic space, similar to eggs of the non-migratory species Leporinus octofasciatus (d, e). Migratory and non-migratory species are indicated as M and N-M, respectively. RESULTS MORPHOLOGICAL IDENTIFICATION A total of 97 ichthyoplankton samples, consisting of 40 eggs and 57 larvae, from the upper Paraná River and the São Francisco River were analysed. Eggs varied in size (mean ± s.e. = 1 00 ± 0 13 mm), colour, shape and integrity state (Fig. 1). Morphological identification according to the perivitellinic space resulted in the classification of 16% as belonging to migratory species as they showed a large perivitellinic space, and 84% as non-migratory due to a reduced perivitellinic space (Table I). Larvae had mean ± s.d. L T of 4 75 ± 0 27 mm and varied greatly in their ontogenetic stage, colour and integrity state (Fig. 2). Classification of the larvae s ontogenetic stage consisted of 9% having embryonic larval yolk-sac development, 65% were at preflexion stage (disappearance of yolk and no notochord flexion), 14% were at flexion stage (showing initial notochord flexion and initial caudal fin rays) and 12% were at postflexion (complete notochord flexion and dorsal-fin rays). None of the larvae were identified to the species level, 3 5% were identified to the genus level (Hoplias sp.), 8 8% to the family and 75 4% to the order level. Detailed taxonomic identification from LGC-PUC laboratory revealed that 77 2% of all larvae Table I. Rates of morphological and DNA barcode identification of 40 fish eggs belonging to migratory or non-migratory species Morphology DNA barcode % n % n Migratory 16 5 67 5 27 Non-migratory 84 35 32 5 13 Total 100 40 100 40
DNA BARCODING OF NEOTROPICAL ICHTHYOPLANKTON 5 Ontogenetic stage Morphology DNA barcode (a) Larval yolk sac Characidae K. moenkausii (b) Preflexion Serrasalmus sp. S. brandtii (c) Flexion Apareiodon sp. A. affinis (d) Postflexion Apareiodon sp. A. affinis (e) Preflexion? A. affinis Fig. 2. Morphological and DNA barcode identification of neotropical fish larvae. Distinct ontogenetic larval stages: (a) larval yolk sac, (b) preflexion, (c) flexion, (d) postflexion and their identification based on morphology and DNA barcoding are shown. Larva (e) is an example of a damaged sample lacking any useful taxonomic characteristic. belonged to the order Characiformes, 1 7% to the order Cyprinodontiformes, 3 5% to the order Gymnotiformes and 5 3% to the order Siluriformes. The family Anostomidae was represented by 1 7%, Characidae by 5 3% and Poecilidae by 1 7% of all larval samples. Due to morphological damage, 12 3% of all larvae were not considered for identification. Larval identification conducted by NUPELIA laboratory allowed the identification of 24 5% to the genus level, 57 9% to family level and 5 3% to order level (Table II). Larvae identified to the genus level consisted of 3 5% Astyanax sp., 8 8% Apareiodon sp., 5 3% Serrasalmus sp.,3 5% Hoplias sp. and 3 5% Eigenmannia sp. Identification to family level found 1 7% Anostomidae, 1 7% Poecilidae and 54 4% Characidae, and 5 3% of larvae were identified to the order Siluriformes. Due to damaged larvae, 12 3% were not considered for identification. Higher taxonomic morphological identification of larvae was strongly correlated to ontogenetic development (Table II). For instance, when considering PUC-LGC s results, no larvae at yolk-sac stage were identified to the genus level, but identified 20% to the family and 80% to order level. At the preflexion stage, 81% of larvae could be identified to order level and 19% were too damaged to be classified. Considering the flexion ontogenetic stage, 12 5% of the larvae could be identified to the genus, 12 5% to the family and 75% to the order level. Taxonomical identification results obtained by NUPELIA identified 60% to order and 40% to family level of larvae at yolk-sac stage. Furthermore, 68% of larvae at preflexion stage were identified to family, 13% to genus level and 19% were not identified due to morphological damage. At flexion ontogenetic stage, 12% of larvae were identified to family and 88% to the
6 R. A. BECKER ET AL. Table II. Percentage accuracies of ichthyoplankton identification to each taxonomic level by morphology (Laboratory LGC-PUC and Laboratory NUPELIA) and DNA barcoding Taxonomic level Yolk sac Preflexion Flexion Postflexion LGC-PUC Species 0 0 0 0 Genus 0 0 12 5 14 Family 20 0 12 5 43 Order 80 81* 75 43 NUPELIA Species 0 0 0 0 Genus 0 13 88 43 Family 40 68* 12 57 Order 60 0 0 0 DNA barcode Species 100 100 100 100 *Some larvae were damaged and therefore not included. LGC-PUC, Conservation Genetics Laboratory, Pontifícia Universidade Católica de Minas Gerais, Brazil; NUPELIA, Ichthyoplankton Laboratory, Núcleo de Pesquisas em Limnologia e Aquicultura, State University of Maringá, Brazil. genus level. At the postflexion stage, 57% of larvae were identified to family and 43% to the genus level (Table II). MOLECULAR IDENTIFICATION (DNA BARCODING) Barcode sequences (684 bp on average) for all 40 eggs and 57 larvae were successfully obtained. Barcodes obtained from eggs and larvae were compared against the GenBank and BOLD databases. For all barcodes, DNA sequence similarities were >99% (Tables SI and SII, Supporting Information). Unexpectedly, only nine eggs were similarly designated to migratory or nonmigratory species using morphological features when compared with DNA barcoding identification, resulting in an accuracy rate of 22 5%. DNA barcoding results showed that 67 5% of all eggs belonged to a single migratory species: Pimelodus maculatus Lacépède 1803 and 32 5% belonged to four non-migratory species: Galeocharax knerii (Steindachner 1879) (12 5%), Leporinus octofasciatus Steindachner 1915 (10%), Leporinus paranensis Garavello & Britski 1987 (2 5%) and Pimelodella meeki Eigenmann 1910 (7 5%) (Table SI, Supporting Information). When considering larval molecular identification, 14 species were recovered: Astyanax altiparanae Garutti & Britski 2000 (3 5%), Bryconamericus stramineus Eigenmann 1908 (1 8%), Knodus moenkhausii (Eigenmann & Kennedy 1903) (36 7%), Piabina argentea Reinhardt 1867 (7%), Apareiodon affinis (Steindachner 1879) (15 8%), Myleus micans (Lütken 1875) (10 5%), Serrasalmus brandtii Lütken 1875 (7%), Leporinus obtusidens (Valenciennes 1837) (1 8%), Hoplias malabaricus (Bloch 1794) (3 5%), Bergiaria westermanni (Lütken 1874) (3 5%), Iheringichthys labrosus (Lütken 1874) (1 8%), Pimelodus fur (Lütken 1874) (1 8%), Eigenmannia virescens (Valenciennes 1836) (3 5%) and Poecilia reticulata Peters 1859 (1 8%) (Table SII, Supporting Information). No discrepancy between DNA barcoding and morphologically identified larvae was observed. The morphologically identified larvae, however, were resolved to the family or genus level (Laboratory LGC-PUC 3 5% and Laboratory NUPELIA 24 6%); by using barcodes, all were identified to species with high sequence similarity (99 100%).
DNA BARCODING OF NEOTROPICAL ICHTHYOPLANKTON 7 DISCUSSION Identification through DNA barcoding overcame the lack of morphological characteristics and ontogenetic variation, allowing the identification of all sampled ichthyoplankton. DNA barcoding reached a greater taxonomic resolution complementing traditional morphological taxonomy. Due to difficulties in ichthyoplankton identification, DNA barcoding provides an important taxonomic tool for regions that already have barcode libraries available, such as the two river basins analysed in this study (Carvalho et al., 2011b; Pereira et al., 2013). The low accuracy rate (25%) observed using morphological techniques when identifying eggs as belonging to migratory or non-migratory species (Table I) clearly demonstrates that the large perivitellinic space for migratory species and reduced perivitellinic space for non-migratory species (Fig. 1) are not informative morphological characteristics. For instance, eggs from the non-migratory species L. octofasciatus, identified by DNA barcoding, showed a developed perivitellinic space [Fig. 1(d)] while the migratory species P. maculatus showed a reduced perivitellinic space [Fig. 1(a)]. Migratory and non-migratory eggs also showed similar shape, colour, size and perivitellinic space (Fig. 1). Moreover, great intraspecific morphological variations were observed for the eggs of P. maculatus [Fig. 1(a), (b), (c), (f)]. In some cases, the presence of collated organic matter [Fig. 1(c)] and damaged morphological characteristics made any morphological taxonomic inference impossible [Fig. 1(c)]. Shao et al. (2002) reported that morphological characteristics were less informative when compared with molecular identification even when more refined morphological techniques for identifying fish eggs were applied (i.e. light microscopy and scanning electron microscopy). Due to the low accuracy rates reported for morphological marine larvae identification when compared with DNA barcoding (Ko et al., 2013), a similar or lower accuracy when dealing with the megadiverse neotropical fish fauna was expected. Despite different levels of taxonomic resolution, disagreement when comparing morphological and DNA barcoding identification was not observed. Larval identification using DNA barcoding, however, resulted in a better taxonomic resolution when compared with traditional morphological taxonomy from both laboratories, especially for the early embryonic phase (i.e. larval yolk-sac stage), as well as allowing damaged sample identification (Table II). For instance, no larvae at larval yolk-sac stage could be identified to the genus level, but when considering the last developmental ontogenetic stage of postflexion, 43% of larvae were correctly identified to the genus level (Table II). Larvae in the yolk-sac ontogenetic stage show very few taxonomically useful morphological characteristics, making their identification to genus level speculative (Fig. 2). In this ontogenetic phase, characteristics are similar between different species, including species belonging to different families (Snyder, 1981; Bialetzki et al., 1998). Specimens that presented damaged morphological characteristics, such as sample larvae (Fig. 2), were successfully identified as A. affinis by DNA barcoding only, which illustrates a recurrent problem when identifying ichthyoplankton solely based on morphological traits. Interestingly, through the use of DNA barcoding, eggs from species not yet registered for this section of the upper Paraná River were detected, such as: K. moenkhausii, L. paranensis and P. meeki, all showed high DNA sequence similarity (99 100%) (Table SI, Supporting Information). Species assessments conducted in the upper Paraná Basin (Nova Ponte Reservoir) have not detected these fishes (unpubl. data). As these are native species already described in the lower parts of the Paraná Basin, they may
8 R. A. BECKER ET AL. occur in the upper region but have not yet been collected by traditional survey methods. Therefore, this is the first record of those species in this region, based solely on molecular data from ichthyoplankton. In conclusion, the ichthyoplankton identification to the species level through DNA barcoding is an efficient tool for the neotropical megadiverse realm, complementing and enhancing traditional morphological taxonomy. The upper Paraná and São Francisco River basins have a large barcode data set available, due to barcode libraries being already available for their ichthyofauna (Carvalho et al., 2011b; Pereira et al., 2013), which explains the great rate of identification of eggs and larvae in the present work to the species level (100% of identification with 99 100% sequences similarities). With the unfolding of the Brazilian Barcode of Life Project (BrBol; http://brbol.org/pt-br/), ichthyoplankton identification by DNA barcoding may be applicable to all river basins in Brazil providing unprecedented information on fish reproduction effects due to damming, detection of species-specific reproduction sites, recovery of hidden fish biodiversity as well as benefiting environmental and fish management conservation in the neotropics. Moreover, the developing of non-destructive DNA extraction from larvae (Alvarado Bremer et al., 2014) will allow the preservation of larvae vouchers and the performance of re-evaluation of diagnostic morphological or meristic characteristics, helping integrate morphological and molecular ichthyoplankton taxonomy. The accuracy of species identification via DNA barcoding, however, is ultimately dependent on the accuracy of morphology-based taxonomic assessment of voucher specimens whose barcodes are available in databases such as GenBank and BOLD. We are grateful to A. Bialetzki and her team for larvae identification performed at NUPELIA; B. Sanches, I. Penido, L. Carvalho, G. N. Salvador, M. L. Pugedo and V. Borges from Genética da Conservação Lab (PUC Minas) for their assistance and helping with sample collection. We thank BrBol/CNPq (564953/2010-5), FAPEMIG, CEMIG (Projeto Peixe Vivo) and CAPES PRO-EQUIPAMENTOS (783380/2013) for financial support. Supporting Information Supporting Information may be found in the online version of this paper: Table SI. Summary of morphological and DNA barcode identification of eggs. Accuracy rate between morphological and barcoding identification is summarized at the end of the table Table SII. Summary of morphological and DNA barcode identification of larvae obtained from the upper Paraná River basin (UP) and the São Francisco River basin (SF). Due to damaged samples, some larvae were not considered for morphological identification ( ). Accuracy rate between morphological and barcoding identification is summarized at the end of the table References Agostinho, A. A., Gomes, L. C., Suzuki, H. I. & Júlio, H. F. Jr. (2003). Migratory fishes of the upper Paraná River basin, Brazil. In Migratory Fishes of South America: Biology, Fisheries and Conservation Status (Carolsfeld, J., Harvey, B., Ross, C. & Baer, A., eds), pp. 19 98. Victoria, BC: World Fisheries Trust. Agostinho, A. A., Marques, E. E., Agostinho, C. S., Almeida, D. D., Oliveira, R. D. & Melo, J. D. (2007). Fish ladder of Lajeado Dam: migrations on one-way routes? Neotropical Ichthyology 5, 121 130. doi: 10.1590/S1679-62252007000200005
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