, Volume 141, Issue 7–9, pp 347–358 | Cite as

Molecular identification of a cryptic species in the Amazonian predatory catfish genus Pseudoplatystoma (Bleeker, 1962) from Peru

  • Carmen García-Dávila
  • Fabrice Duponchelle
  • Diana Castro-Ruiz
  • José Villacorta
  • Sophie Quérouil
  • Werner Chota-Macuyama
  • Jesus Núñez
  • Uwe Römer
  • Fernando Carvajal-Vallejos
  • Jean-François RennoEmail author


Pseudoplatystoma species are highly prized South American Pimelodid migratory catfishes. Until recently, their taxonomy was not clearly established, with discrepancies between morphological and molecular analyses. Here, Pseudoplatystoma species from the Peruvian Amazon were characterized at the molecular level from a sample representing the observed range of their color pattern variations in the study area. Analyses were performed using seven microsatellite loci for 103 specimens and, for part of them (52), using sequences of two regions of their mitochondrial genome [Cytochrome Oxidase subunit I (COI) and Control Region (CR)]. Factorial correspondence analysis and assignment tests based on microsatellite polymorphism showed that the specimens originally identified as P. punctifer belonged to two different gene pools highly differentiated from P. tigrinum. Morphological examination identified two different morphotypes (with and without black stripes), suggesting the existence of two distinct taxa within P. punctifer. This result was corroborated by the ML tree based on CR sequences, where all individuals but four clustered in a similar way as in the FCA and Bayesian assignment tests. For these four individuals, mitochondrial introgression or retention of ancestral polymorphism was likely. In contrast, the ML tree based on COI sequences showed that reciprocal monophyly was not yet achieved for this marker for the two P. punctifer taxa. The existence of three sympatric species of Pseudoplatystoma in the Peruvian Amazon is discussed in relation to their molecular characteristics, color patterns and ecology. Evolutionary scenarios regarding their divergence are hypothesized.


Microsatellites Control Region Barcoding Migratory catfish 



This study was carried out within the Laboratoire Mixte International “Evolution et Domestication de l’Ichtyofaune Amazonienne” (LMI-EDIA) developed by the Instituto de Investigaciones de la Amazonia Peruana (IIAP) and the Institut Français de Recherche pour le Développement (IRD), both of which are part of the network Red de Investigación sobre la Ictiofauna Amazónica (RIIA Financial support was provided by INCAGRO (Inovación para el Agro Peruano, subproject “Breeding and intensive production of fingerlings of Doncella Pseudoplatystoma fasciatum (Linnaeus, 1776) in the Peruvian Amazon”), IIAP and IRD.


  1. Agnèse J-F, Zentz F, Legros O, Sellos D (2006) Phylogenetic relationships and phylogeography of the Killifish species of the subgenus Chromaphyosemion (Radda, 1971) in West Africa, inferred from mitochondrial DNA sequences. Mol Phylogenet Evol 40:332–346PubMedCrossRefGoogle Scholar
  2. Agudelo E, Salinas Y, Sanchez CL, Munoz-Sosa DL, Alonso JC, Arteaga ME, Rodriguez OJ, Anzola NR, Acosta LE, Nunez M, Valdes H (2000) Bagres de la Amazonia Colombiana: un Recurso sin Fronteras. SINCHI. Programa de Ecosistemas Acuaticos. Editorial Scipto Ltda.: Santa Fé de Bogota D.C., ColombiaGoogle Scholar
  3. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In Petrov BN, Csaki F (eds) 2nd international symposium on information theory. Akadémia Kiado, Budapest, pp 267–281Google Scholar
  4. Albert JS, Reis RE (eds) (2011) Historical biogeography of Neotropical freshwater fishes. University of California Press, BerkeleyGoogle Scholar
  5. Aquilino S, Tango J, Fontanilla I, Pagulayan R, Basiao Z, Ong P, Quilang P (2011) DNA barcoding of the ichthyofauna of Taal Lake, Philippines. Mol Ecol Resour 11:612–619PubMedCrossRefGoogle Scholar
  6. Ardura A, Pola IG, Ginuino I, Gomes V, Garcia-Vásquez E (2010) Application of barcoding to Amazonian commercial fish labelling. Food Res Int 43:1549–1552CrossRefGoogle Scholar
  7. Asgharian H, Sahafi HH, Ardalan AA, Shekarriz S, Elahi E (2011) Cytochrome c oxidase subunit 1 barcode data of fish of the Nayband National Park in the Persian Gulf and analysis using meta-data flag several cryptic species. Mol Ecol Resour 11:461–472PubMedCrossRefGoogle Scholar
  8. Baras E, Montalvan Naranjos GV, Silva del Aguila DV, Koo FC, Dugué R, Chávez C, Duponchelle F, Renno J-F, García-Dávila CC, Nuñez J (2011a) Ontogenetic variation of food intake and gut evacuation rate in larvae of the doncella Pseudoplatystoma punctifer, as measured using a non-destructive method. Aquac Res 24:379–390Google Scholar
  9. Baras E, Silva del Aguila DV, Montalvan Naranjos GV, Dugué R, Koo FC, Duponchelle F, Renno J-F, García-Dávila C, Nuñez J (2011b) How many meals a day to minimize cannibalism when rearing larvae of the Amazonian catfish Pseudoplatystoma punctifer? The cannibal’s point of view. Aquat Living Resour 24:379–390CrossRefGoogle Scholar
  10. Barthem R, Goulding M (1997) The catfish connection. Ecology, migration and conservation of Amazon predators. Columbia University Press, New YorkGoogle Scholar
  11. Barthem R, Goulding M (2007) Un ecosistema inesperado: la Amazonía revelada por la pesca. Museu Paraense Emilio Goeldi, Amazon Conservation Association (ACA), LimaGoogle Scholar
  12. Bartley DM, Rana K, Immink AJ (2000) The use of inter-specific hybrids in aquaculture and fisheries. Rev Fish Biol Fisher 10:325–337CrossRefGoogle Scholar
  13. Belkhir K, Bonhomme F (2002) PARTITION ML: a maximum likelihood estimation of the best partition of a sample into panmictic units. Université Montpellier 2, Montpellier, FranceGoogle Scholar
  14. Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F (2004) GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. Montpellier, France: Laboratoire Génome, Populations, Interactions, CNRS UMR 5000, Université Montpellier IIGoogle Scholar
  15. Buitrago-Suarez UA, Burr BM (2007) Taxonomy of the catfish genus Pseudoplatystoma Bleeker (Siluriformes: Pimelodidae) with recognition of eight species. Zootaxa 1512:1–38Google Scholar
  16. Cañas CM (2000) Evaluación de los recursos pesqueros en la Provincia de Tambopata, Madre de Dios (Julio 1995-Diciembre 1998): Conservación Internacional-Peru, p 68Google Scholar
  17. Carvalho-Costa LF, Piorski NM, Willis SC, Galetti PM Jr, Ortí G (2011) Molecular systematics of the neotropical shovelnose catfish genus Pseudoplatystoma Bleeker 1862 based on nuclear and mtDNA markers. Mol Phylogenet Evol 59:177–194PubMedCrossRefGoogle Scholar
  18. Castelnau Fd (1855) Animaux nouveaux ou rares recueillis pendant l’expedition dans les parties centrales de l’Amerique du Sud :de Rio de Janeiro a Lima, et de Lima au Para : exécutée par ordre du gouvernement Français pendant les années 1843 à 1847. P. Bertrand, ParísGoogle Scholar
  19. Chong SSC, Khoo HW (1987) Abbreviated larval development of the freshwater prawn, Macrobrachium pilimanus (De Man, 1879) (Decapoda, Palaemonidae), reared in the laboratory. J Nat Hist 21:763–774CrossRefGoogle Scholar
  20. Doyle JJ, Doyle JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19:11–15Google Scholar
  21. Frankham R, Ballou J, Briscoe D (2004) A primer of conservation genetics. University of Cambridge Press, CambridgeCrossRefGoogle Scholar
  22. Garcia A, Tello S, Vargas G, Duponchelle F (2009) Patterns of commercial fish landings in the Loreto region (Peruvian Amazon) between 1984 and 2006. Fish Physiol Biochem 35:53–67PubMedCrossRefGoogle Scholar
  23. Guindon S, Gascuel O (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 52:696–704PubMedCrossRefGoogle Scholar
  24. Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucl Acids Symp Ser 41:95–98Google Scholar
  25. Harrington RC, Near TJ (2012) Phylogenetic and coalescent strategies of species delimitation in snubnose darters (Percidae: Etheostoma). Syst Biol 61:63–79PubMedCrossRefGoogle Scholar
  26. Hartl D, Clark A (1997) Principles of population genetics. Sinauer Associates, Inc. Publishers Sunderland, MassachussettsGoogle Scholar
  27. Hebert PDN, Penton EH, Burns JM, Janzen DH, Hallwachs W (2004a) Ten species in one: DNA barcoding reveals cryptic species in the Neotropical skipper butterfly Astraptes fulgerator. P Natl Acad Sci USA 101:14812–14817CrossRefGoogle Scholar
  28. Hebert PDN, Stoeckle MY, Zemlak TS, Francis CM (2004b) Identification of birds through DNA barcodes. Public Libr Sci 2:1657–1663Google Scholar
  29. Hoorn C, Guerreo J, Sarmiento GA, Lorente MA (1995) Andean tectonics as a cause for changing drainage patterns in Miocene northern South America. Geology 23:237–240CrossRefGoogle Scholar
  30. Hubert N, Renno J-F (2006) Historical biogeography of South American freshwater fishes. J Biogeogr 33(8):1414–1436 Google Scholar
  31. Hubert N, Duponchelle F, Nuñez J, Paugy D, Garcia-Davila C, Renno J-F (2007) Phylogeography of the piranhas genera Serrasalmus and Pygocentrus implications for the diversification of the Neotropical Ichtyofauna. Mol Ecol 16:2115–2136PubMedCrossRefGoogle Scholar
  32. Hubert N, Hanner R, Holm E, Mandrak NE, Taylor E, Burridge M, Watkinson D, Dumont P, Curry A, Bentzen P, Zhang J, April J, Bernatchez L (2008a) Identifying Canadian freshwater fishes through DNA barcodes. PLoS ONE 3:e2490PubMedCrossRefGoogle Scholar
  33. Hubert N, Torrico JP, Bonhomme F, Renno J-F (2008b) Species polyphyly and mtDNA introgression among three Serrasalmus sister-species. Mol Phylogenet Evol 46:375–381PubMedCrossRefGoogle Scholar
  34. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science. New Ser 220(4598):671–680Google Scholar
  35. Lakra WS, Verma MS, Goswami M, Lal KK, Mohindra V, Punia P, Gopalakrishnan A, Singh KV, Ward RD, Hebert P (2011) DNA barcoding Indian marine fishes. Mol Ecol Resour 11:60–71PubMedCrossRefGoogle Scholar
  36. Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451–1452PubMedCrossRefGoogle Scholar
  37. Loubens G, Panfili J (2000) Biologie de Pseudoplatystoma fasciatum et P. tigrinum (Teleostei: Pimelodidae) dans le bassin du Mamoré. Ichthyol Explor Freshw 11:13–34Google Scholar
  38. Lucas MC, Baras E (2001) Migration of freshwater fishes. Blackwell Science Ltd., OxfordCrossRefGoogle Scholar
  39. Lundberg JG (1998) The temporal context for diversification of Neotropical fishes. In: Malabarba LR, Reis RE, Vari RP, Lucena CAS, Lucena ZMS (eds) Phylogeny and classification of Neotropical fishes. EDIPUCRS, Porto AlegreGoogle Scholar
  40. Mayr E (1942) Systematics and the origin of species, from the view point of a zoologist. Columbia University Press, USAGoogle Scholar
  41. Meldgaard T, Crivelli A, Jesensek D, Poizat G, Rubin J-F, Berrebi P (2007) Hybridization mechanisms between the endangered marble trout (Salmo marmoratus) and the brown trout (Salmo trutta) as revealed by in-stream experiments. Biol Conserv 136:602–611CrossRefGoogle Scholar
  42. Myers RA, Baum JK, Shepherd TD, Powers SP, Peterson CH (2007) Cascading effects of the loss of apex predatory sharks from a coastal ocean. Science 315:1846–1850PubMedCrossRefGoogle Scholar
  43. Nuñez J, Castro D, Fernández C, Dugué R, Chu-Koo F, Duponchelle F, García C, Renno J-F (2011) Hatching rate and larval growth variations in Pseudoplatystoma punctifer: maternal and paternal effects. Aquac Res 42:764–775CrossRefGoogle Scholar
  44. Pace ML, Cole JJ, Carpenter SR, Kitchell JF (1999) Trophic cascades revealed in diverse ecosystems. Trends Ecol Evol 14:483–488PubMedCrossRefGoogle Scholar
  45. Paradis E (2006) Analysis of phylogenetics and evolution with R. Springer, New YorkGoogle Scholar
  46. Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290PubMedCrossRefGoogle Scholar
  47. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  48. Reid S (1983) La biología de los bagres rayados Pseudoplatystoma fasciatum y P. tigrinum en la cuenca del rio Apure, Venezuela. Revis UNELLEZ Cien Tecnol 1:13–41Google Scholar
  49. Renno J-F, Hubert N, Torrico JP, Duponchelle F, Nunez J, Garcia-Davila C, Willis S, Desmarais E (2006) Phylogeography of Cichla (Cichlidae) in the Upper Madera basin (Bolivian Amazon). Mol Phylogenet Evol 41:503–510PubMedCrossRefGoogle Scholar
  50. Revaldaves E, Pereira L, Foresti F, Oliveira C (2005) Isolation and characterization of microsatellite loci in Pseudoplatystoma corruscans (Siluriformes: Pimelodidae). Mol Ecol Notes 5:463–465CrossRefGoogle Scholar
  51. Rocha-Olivares A, Fleeger JW, Foltz DW (2001) Decoupling of molecular and morphological evolution in deep lineages of a meiobenthic harpacticoid copepod. Mol Biol Evol 18(6):1088–1102PubMedCrossRefGoogle Scholar
  52. Römer U (2001) Influence of temperature on fertility, growth rates, and reproductive success on selected species of Apistogramma (Teleostei, Cichlidae). Verhandlungen der Gesellschaft fuer Ichthyologie 2:87–106Google Scholar
  53. Römer U (2006) Cichlid Attlas Volume 2. Mergus Verlag, MelleGoogle Scholar
  54. Römer U, Beisenherz W (2006) Are sexual behaviour and other traits of behaviour in Apistogramma species (Teleostei: Cichlidae) suitable for taxonomic classification? In: Greven H, Riehl R (eds) Verhalten der Aquarienfische 2. Tetra-Verlag, Berlin, pp 147–158Google Scholar
  55. Römer U, Hahn I (2008) Apistogramma barlowi: description of a new species of facultative mouth-breeding cichlid species (Teleostei: Perciformes: Geophaginae) from Northern Peru. Vert Zool 58:49–66Google Scholar
  56. Serra-Pereira B, Moura T, Griffiths A, Gordo L, Figueiredo I (2010) Molecular barcoding of skates (Chondrichthyes: Rajidae) from the southern Northeast Atlantic. Zool Scr 40:76–84CrossRefGoogle Scholar
  57. Smith PJ, Steinke D, McMillan PJ, Stewart AL, McVeagh SM, Diaz de Astarloa JM, Welsford D, Ward RD (2011) DNA barcoding highlights a cryptic species of grenadier Macrourus in the Southern Ocean. J Fish Biol 78:355–365PubMedCrossRefGoogle Scholar
  58. Smouse PE, Waples RS, Tworek JA (1990) A mixed fishery model for use with incomplete source population data. Can J Fish Aquat Sci 47:620–634CrossRefGoogle Scholar
  59. Steinke D, Zemlak TS, Hebert PDN (2009) Barcoding Nemo: DNA-based identifications for the ornamental fish trade. PLoS ONE 4:e6300PubMedCrossRefGoogle Scholar
  60. Tello S, Bayley PB (2001) La pesquería comercial de Loreto con énfasis en el análisis de la elación entre captura y esfuerzo pesquero de la flota comercial de Iquitos, cuenca del Amazonas (Perú). Folia Amazónica 12:123–139Google Scholar
  61. Toffoli D, Hrbek T, Góes de Araújo ML, Pinto de Almeida M, Charvet-Almeida P, Farias I (2008) A test of the utility of DNA barcoding in the radiation of the freshwater stingray genus Potamotrygon (Potamotrygonidae, Myliobatiformes). Genet Mol Biol 31(1 suppl):324–336CrossRefGoogle Scholar
  62. Torrico J-P, Hubert N, Desmarais E, Duponchelle F, Nuñez Rodriguez J, Montoya-Burgos J, Garcia-Davila C, Carvajal F, Grajales AA, Bonhomme F, Renno J-F (2009) Molecular phylogeny of the Pseudoplatystoma (Bleeker, 1862): biogeographic and evolutionary implications. Mol Phylogenet Evol 51:588–594PubMedCrossRefGoogle Scholar
  63. Ward RD, Hanner R, Hebert PDN (2009) The campaign to DNA barcode all fishes, FISHBOL. J Fish Biol 74:329–356PubMedCrossRefGoogle Scholar
  64. Winemiller KO (2005) Floodplain river food webs: generalizations and implications for fisheries management. In: Welcomme RL, Petr T (eds) Proceedings of the Second International Symposium on the Management of Large Rivers for Fisheries Phnom Penh. Mekong River Commission, Cambodia, pp 285–312Google Scholar
  65. Winemiller KO, Jepsen DB (1998) Effects of seasonality and fish movements on tropical river food webs. J Fish Biol 53:267–296CrossRefGoogle Scholar
  66. Wong LL, Peatman E, Lu J, Kucuktas H, He S, Zhou C, Na-nakorn U, Liu Z (2011) DNA barcoding of catfish: species authentication and phylogenetic assessment. PLoS ONE 6:e17812PubMedCrossRefGoogle Scholar
  67. Zhang JB, Hanner R (2011) DNA barcoding is a useful tool for the identification of marine fishes from Japan. Biochem Syst Ecol 39:31–42CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Carmen García-Dávila
    • 1
    • 2
  • Fabrice Duponchelle
    • 1
    • 3
  • Diana Castro-Ruiz
    • 1
    • 2
  • José Villacorta
    • 2
  • Sophie Quérouil
    • 1
    • 3
  • Werner Chota-Macuyama
    • 1
    • 2
  • Jesus Núñez
    • 1
    • 3
  • Uwe Römer
    • 1
    • 4
    • 5
  • Fernando Carvajal-Vallejos
    • 1
    • 6
    • 7
  • Jean-François Renno
    • 1
    • 3
    Email author
  1. 1.Laboratoire Mixte International-Evolution et Domestication de l’Ichtyofaune Amazonienne (LMI-EDIA)IquitosPeru
  2. 2.Laboratorio de Biología y Genética Molecular (LBGM), Programa para el Uso y Conservación del Agua y sus Recursos (AQUAREC)Instituto de Investigaciones de la Amazonía Peruana (IIAP)IquitosPeru
  3. 3.Institut de Recherche pour le Développement (IRD), Institut des Sciences de l’Evolution de Montpellier (UMR 226-ISEM)Université Montpellier 2Montpellier Cedex 5France
  4. 4.Department of Geo-Sciences Institute for BiogeographyUniversity of TrierTrierGermany
  5. 5.GüterslohGermany
  6. 6.Unidad de Limnología y Recursos AcuáticosUniversidad Mayor San SimónCochabambaBolivia
  7. 7.Asociación FAUNAGUACochabambaBolivia

Personalised recommendations