Metabarcoding: una herramienta prometedora para el estudio de la ecología trófica de peces mexicanos

Autores/as

DOI:

https://doi.org/10.22201/ib.20078706e.2023.94.4855

Palabras clave:

Biodiversidad, Código de barras, Dietas, Genes, Nicho trófico

Resumen

El papel de los peces en la dinámica trófica de los ecosistemas acuáticos se ha estudiado usando diferentes métodos que permiten determinar su dieta y posición trófica (inspección visual del contenido estomacal y heces, isótopos estables, secuenciación de ADN). Con los avances tecnológicos en la secuenciación de alto rendimiento del ADN, el uso del método de metabarcoding se ha incrementado en los últimos años, demostrando tener mayor precisión y alcance taxonómico que otros métodos, además de que permite el análisis simultáneo de un mayor número de muestras en un menor tiempo. En esta revisión, se describen los pasos del método de metabarcoding, discutiendo sus ventajas y limitaciones, así como las alternativas experimentales y analíticas propuestas para atender dichas limitaciones. Además, se presenta una síntesis del estado del conocimiento del método de metabarcoding aplicado al análisis de la ecología trófica de peces para entender los alcances y las limitaciones de este método en México.

Biografía del autor/a

Nancy Calderón-Cortés, Universidad Nacional Autónoma de México

Profesor Ordinario de Carrera Titular A de T.C., Escuela Nacional de Estudios Superiores Unidad Morelia. Laboratorio de Ecología Molecular.

Citas

Albaina, A., Aguirre, M., Abad, D., Santos, M. y Estonba, A. (2016). 18S rRNA V9 metabarcoding for diet characterization: a critical evaluation with two sympatric zooplanktivorous fish species. Ecology and Evolution, 6, 1809–1824. https://doi.org/10.1002/ece3.1986

Alberdi, A., Aizpurua, O., Bohmann, K., Gopalakrishnan, S., Lynggaard, C., Nielsen, M. et al. (2019). Promises and pitfalls of using high‐throughput sequencing for diet analysis. Molecular Ecology Resources, 19, 327–348. https://doi.org/10.1111/1755-0998.12960

Anantharaman, K., Brown, C. T., Hug, L. A., Sharon, I., Castelle, C. J., Probst, A. J. et al. (2016). Thousands of microbial genomes shed light on interconnected bio- geochemical processes in an aquifer system. Nature Communications, 7, 13219. https://doi.org/10.1038/ncomms13219

Arranz, V., Pearman, W. S., Aguirre, J. D. y Liggins, L. (2020). MARES, a replicable pipeline and curated reference database for marine eukaryote metabarcoding. Scientific Data, 7, 1–8. https://doi.org/10.1038/s41597-020-0549-9

Bachiller, E., Albo-Puigserver, M., Giménez, J., Pennino, M. G., Marí-Mena, N., Esteban, A. et al. (2020). A trophic latitudinal gradient revealed in anchovy and sardine from Western Mediterranean Sea using a multi-proxy approach. Scientific Reports, 10, 17598. https://doi.org/10.1038/s41598-020-74602-y

Bachiller, E., Gimenéz, J., Albo-Puigserver, M., Pennino, M. G., Marí-Mena, N., Esteban, A. et al. (2021). Trophic niche overlap between round safinell (Sardinella aurita) and sympatric pelagic fish species in the Western Mediterranean. Ecology and Evolution, 11, 16126–16142. https://doi.org/10.1002/ece3.8293

Ballesteros-Nova, N.E., Pérez-Rodríguez, R., Betrán-López, R.G. y Domínguez-Domínguez, O. (2019). Genetic differentiation in the southern population of the fathead minnow Pimephales promelas rafinesque (Actinopterygii: Cyprinidae). PeerJ, 7, e6224. https://doi.org/10.7717/peerj.6224

Beltrán-López, R. G., Domínguez-Domínguez, O., Guerrero, J. A., Corona-Santiago, D. K., Mejía-Mojica, H. y Doadrio, I. (2017). Phylogeny and taxonomy of the genus Ilyodon Eigenmann, 1907 (Teleostei: Goodeidae), based on mitochondrial and nuclear DNA sequences. Journal of Zoological Systematics and Evolutionary Research, 55, 340–355. https://doi.org/10.1111/jzs.12175

Beltrán-López, R. G., Domínguez-Domínguez, O., Pérez-Rodríguez, R., Kyle, P. y Doadrio, I. (2018). Evolving in the highlands: the case of the Neotropical Lerma live-bearing Poeciliopsis infans (Wolman, 1984) (Cyprinodontiformes: Poeciliidae) in Central Mexico. BMC Evololutionary Biology, 18, 56. https://doi.org/0.1186/s12862-018-1172-7

Berry, O., Bulman, C., Bunce, M., Coghlan, M., Murray, D. C. y Ward, R. D. (2015). Comparison of morphological and DNA metabarcoding analyses of diets in exploited marine fishes. Marine Ecology Progress Series, 540, 167–181. https://doi.org/10.3354/meps11524

Bessey, C., Jarman, S. N., Stat, M., Rohner, C. A., Bunce, M., Koziol, A. et al. (2019). DNA metabarcoding assays reveal a diverse prey assemblage for Mobula rays in the Bohol Sea, Philippines. Ecology and Evolution, 9, 2459–2474. https://doi.org/10.1002/ece3.4858

Bonato, K. O., Silva, P. C., Carvalho, R. F. y Malabarba, L. R. (2022). Trophic interactions of vampire catfishes (Siluriformes: Vandelliinae) revealed by metabarcoding analysis of stomach contents. Freshwater Biology, 67, 542–548. https://doi.org/10.1111/fwb.13861

Bowser, A. K., Diamond, A. W. y Addison, J. A. (2013). From puffins to plankton: A DNA-based analysis of a seabird food chain in the northern Gulf of Maine. Plos One, 8, e83152. https://doi.org/10.1371/journal.pone.0083152

Brandl, S. J., Casey, J. M. y Meyer, C. P. (2020). Dietary and habitat niche partitioning in congeneric cryptobenthic reef fish species. Coral Reefs, 39, 305–317. https://doi.org/10.1007/s00338-020-01892-z

de Bruyn, M., Barbato, M., DiBattista, J. D. y Broadhurst, M. K. Secondary predation constrains DNA-based diet reconstruction in two threatened shark species. Scientific Reports, 11, 18350. https://doi.org/10.1038/s41598-021-96856-w

Bunch, A. J., Carlson, K. B., Hoogakker, F. J., Plough, L. V. y Evans, H. K. (2021). Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus Mitchill, 1815) early life stage consumption evidenced by high-throughput DNA sequencing. Journal of Applied Ichthyology, 37, 12–19. https://doi.org/10.1111/jai.14153

Carlisle, A. B., Andruszkiewicz, A. E., Kim, S. L., Meyer, L., Port, J., Scherrer, S. et al. (2021). Integrating multiple chemical tracers to elucidate the diet and habitat of Cookiecutters sharks. Scientific Reports, 11, 11809. https://doi.org/10.1038/s41598-021-89903-z

Cartes, J. E., Soler-Membrives, A., Stefanescu, C., Lombarte, A. y Carrassón, M. (2016). Contributions of allochthonous inputs of food to the diets of benthopelagic fish over the northwest Mediterranean slope (to 2300 m). Deep Sea Research Part I: Oceanographic Research Papers, 109, 123–136. https://doi.org/10.1016/j.dsr.2015.11.001

Casey, J. M., Meyer, C. P., Morat, F., Brandl, S. J., Planes, S. y Parravicini, V. (2019). Reconstructing hyper diverse food webs: gut content metabarcoding as a tool to disentangle trophic interactions on coral reefs. Methods in Ecology and Evolution, 10, 1157–1170. https://doi.org/10.1111/2041-210X.13206

Castro-Sanguino, C. y Sánchez, J. A. (2012). Dispersal of Symbiodinium by the stoplight parrotfish Sparisoma viride. Biology Letters, 8, 282–286. https://doi.org/10.1098/rsbl.2011.0836

CBOL, P. W. G. (2009). A DNA barcode for land plants. Proceedings of the National Academy of Sciences, 106, 12794–12797. https://doi.org/10.1073/pnas.0905845106

Clarke, L. J., Trebilco, R., Walters, A., Polanowski, A. M. y Deagle, B. E. (2020). DNA-based diet analysis of mesopelagic fish from the southern Kerguelen Axis. Deep Sea Research Part II, 174, 104494. https://doi.org/10.1016/j.dsr2.2018.09.001

Collins, R. A., Bakker, J., Wangensteen, O. S., Soto, A. Z., Corrigan, L., Sims, D. W. et al. (2019). Non-specific amplification compromises environmental DNA metabarcoding with COI. Methods in Ecology and Evolution, 10, 1985–2001. https://doi.org/10.1111/2041-210X.13276

Corse, E., Meglècz, E., Archambaud, G., Ardisson, M., Martin, J. F., Tugard, C. et al. (2017). A from-benchtop-to-desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding studies. Molecular Ecology Resources, 17, e146–e159. https://doi.org/10.1111/1755-0998.12703

Corse, E., Tougard, C., Archambaud‐Suard, G., Agnèse, J. F., Messu-Mandeng, F. D., Bilong-Bilong, C. F. et al. (2019). One‐locus‐several‐primers: a strategy to improve the taxonomic and haplotypic coverage in diet metabarcoding studies. Ecology and Evolution, 9, 4603–4620. https://doi.org/10.1002/ece3.5063

Creer, S., Deiner, K., Frey, S., Porazinska, D., Taberlet, P., Thomas, W. K. et al. (2016). The ecologist´s field guide to sequence-based identification of biodiversity. Methods in Ecology and Evolution, 7, 1008–1018. https://doi.org/10.1111/2041-210X.12574

Cuff, J. P., Windsor, F. M., Tercel, M. P. T. G., Kitson, J. J. N. y Evans, D. M. (2022). Overcoming the pitfalls of merging dietary metabarcoding into ecological networks. Methods in Ecology and Evolution, 13, 545–559. https://doi.org/10.1111/2041-210X.13796

da Silveira, E. L., Semmar, N., Cartes, J. E., Tuset, V. M., Lombarte, A., Ballester, E. L. C. et al. (2020). Methods for trophic ecology assessment in fishes: a critical review of stomach analyses. Reviews in Fisheries Science y Aquaculture, 28, 71–106. https://doi.org/10.1080/23308249.2019.1678013

Dahl, K. A., Patterson, W. F., Robertson, A. y Ortmann, A. C. (2017). DNA barcoding significantly improves resolution of invasive lionfish diet in the Northern Gulf of Mexico. Biological Invasions, 19, 1917–1933. https://doi.org/10.1007/s10530-017-1407-3

Deagle, B. E., Eveson, J. P. y Jarman, S. N. (2006). Quantification of damage in DNA recovered from highly degraded samples – a case study on DNA in feces. Frontiers in Zoology, 3, 11. https://doi.org/10.1186/1742-9994-3-11

Deagle, B. E., Jarman, S. N., Coissac, E., Pompanon, F. y Taberlet, P. (2014). DNA metarbocoding and the cytochrome C oxidase subunit I marker: not a perfect match. Biology Letters, 10, 20140562. https://doi.org/10.1098/rsbl.2014.0562

Deagle, B. E., Thomas, A. C., McInnes, J. C., Clarke, L. J., Vesterinen, E. J., Clare, E. L. et al. (2019). Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? Molecular Ecology, 28, 391–406. https://doi.org/10.1111/mec.14734

de Sousa, L. L., Xavier, R., Costa, V., Humpries, E., Trueman, C., Rosa, R. et al. (2016). DNA barcoding identifies a cosmopolitan diet in the ocean sunfish. Scientific Reports, 6, 28762. https://doi.org/10.1038/srep28762

de Sousa, L. L., Silva, S. M. y Xavier, R. (2019). DNA metabarcoding in diet studies: unveiling ecological aspects in aquatic and terrestrial ecosystems. Environmental DNA, 1, 199–214. https://doi.org/10.1002/edn3.27

Devloo-Delva, F., Huerlimann, R., Chau, G., Matley, J. K., Heupel, M. R., Simpfendorfer, C. A. et al. (2018). How does marker choice affect your diet analysis: comparing genetic markers and digestion levels for diet metabarcoding of tropical-reef piscivores? Marine and Freshwater Research, 70, 8–18. https://doi.org/10.1071/MF17209

Dickie, I. A., Boyer, S., Buckley, H. L., Duncan, R. P., Gardner, P. P., Hogg, I. D. et al. (2018). Towards robust and repeatable sampling methods in eDNA-based studies. Molecular Ecology Resources, 18, 940–952. https://doi.org/10.1111/1755-0998.12907

Doble, C. J., Hipperson, H., Salzburger, W., Horsburgh, G. J., Mwita, C., Murrell, D. J. et al. (2019). Testing the performance of environmental DNA metabarcoding for surveying highly diverse tropical fish communities: a case study from Lake Tanganyika. Environmental DNA, 2, 24–41. https://doi.org/10.1002/edn3.43

Domínguez-Domínguez, O., Doadrio, I. y Pérez-Ponce de León, G. (2006). Historical biogeography of some river basins in central Mexico evidenced by their goodeine freshwater fishes: a preliminary hypothesis using secondary Brooks parsimony analysis. Journal of Biogeography, 33, 1437–1447.

https://doi.org/10.1111/j.1365-2699.2006.01526.x

Ducotterd, C., Crovadore, J., Lefort, F., Rubin, J. F. y Ursenbacher, S. (2021). A powerful long metabarcoding method for the determination of complex diet from fecal analysis of the European pond turtle (Emys orbicularis, L. 1758). Molecular Ecology Resources, 21, 433–447. https://doi.org/10.1111/1755-0998.13277

Elbrecht, V., Taberlet, P., Dejean, T., Valentini, A., Usseglio-Polatera, P., Beisel, J. N. et al. (2016). Testing the potential of a ribosomal 16S marker for DNA metabarcoding of insects. PeerJ, 4, e1966. https://doi.org/10.7287/peerj.preprints.1855v1

Elbrecht, V. y Leese, F. (2017). Validation and development of COI metabarcoding primers for freshwater macroinvertebrate bioassessment. Frontiers in Environmental Science, 5, 11. https://doi.org/10.3389/fenvs.2017.00011

Elbrecht, V., Braukmann, T. W. A., Ivanova, N. V., Prosser, S. W. J., Hajbabaei, M., Wright, M. et al. (2019). Validation of COI metabarcoding primers for terrestrial arthropods. PeerJ, 7, e7745. https://doi.org/10.7717/peerj.7745

Espinosa-Pérez, H. (2014). Biodiversidad de peces en México. Revista Mexicana de Biodiversidad, 85 (Supl.), S450–S459. https://doi.org/10.7550/rmb.32264

Evans, H. K., Bunch, A. J., Schmitt, J. D., Hoogakker, F. J. y Carlson, K. B. (2021). High-throughput sequencing outperforms traditional morphological methods in Blue Catfish diet analysis and reveals novel insights into diet ecology. Ecology and Evolution, 11, 5584–5597. https://doi.org/10.1002/ece3.7460

Finlay, J. C., Doucett, R. R. y McNeely, C. (2010). Tracing energy flow in stream food webs using stable isotopes of hydrogen. Freshwater Biology, 55, 941–951. https://doi.org/10.1111/j.1365-2427.2009.02327.x

Folmer, O., Black, M., Hoeh, W., Lutz, R. y Vrijenhoek, R. (1994). DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Molecular Marine Biology and Biotechnology, 3, 294–299.

Freeland, J. R. (2017). The importance of molecular markers and primer design when characterizing biodiversity from environmental DNA. Genome/National Research Council Canada = Genome/Conseil National De Recherches Canada, 60, 358–374. https://doi.org/10.1139/gen-2016-0100

French, B. J., Lim, Y. W., Zglicznski, B. J., Edwards, R. A., Rohwer, F. y Sandin, S. A. (2020). Decoding diversity in a coral reef fish species complex with restricted range using metagenomic sequencing of gut contents. Ecology and Evolution, 10, 3413–3423. https://doi.org/10.1002/ece3.6138

Gajdzik, L., DeCarlo, T. M., Koziol, A., Mousavi-Derazmahalleh, M., Coghlan, M., Power, M. W. et al. (2021). Climate-assisted persistence of topical fish vagrants in temperate marine ecosystems. Communications Biology, 4, 1231. https://doi.org/10.1038/s42003-021-02733-7

Galan, M., Pons, J. B., Tournayre, O., Pierre, E., Leuchtmann, M., Pontier, D. et al. (2018). Metabarcoding for the parallel identification of several hundred predators and their preys: application to bat species diet analysis. Molecular Ecology Resources, 18, 474–489. https://doi.org/10.1101/155721

Gallet, A., Koubbi, P., Léger, N., Scheifler, M., Ruiz-Rofriguez, M., Suzuki, M. T. et al. (2019). Low-diversity bacterial microbiota in Southern Ocean representatives of lanternfish general Electrona, Protomyctophum and Gymnoscopelus (family Myctophidae). Plos One, 14, e0226159. https://doi.org/10.1371/journal.pone.0226159

García-Morales, A. E., Domínguez-Domínguez, O. y Elías-Gutiérrez, M. (2021). Uncovering hidden diversity; three new species of the Keratella genus (Rotifera, Monogononta, Brachionidae) of high-altitude water systems from central Mexico. Diversity, 13, 676. https://doi.org/10.3390/d13120676

Gillet, F., Tiouchichine M. L., Galan, M., Blanc, F., Némoz, M., Aulagnier, S. et al. (2015). A new method to identify the endangered Pyrenean desman (Galemys pyrenaicus) and study its diet, using next generation sequencing from feces. Mammalian Biology, 80, 505–509. https://doi.org/0.1016/j.mambio.2015.08.002

Guillerault, N., Bouletreau, S., Iribar, A., Valentini, A. y Santoul, F. (2017). Application of DNA metabarcoding of feces to identify European catfish Silurus glanis diet. Journal of Fish Biology, 90, 2214–2219. https://doi.org/10.1111/jfb.13294

Günther, B., Fromentin, J. M., Metral, L. y Arnaud-Haond, S. (2021). Metabarcoding confirms the opportunistic foraging behavior of Atlantic bluefin tuna and reveals the importance of gelatinous prey. PeerJ, 9, e111757. https://doi.org/10.7717/peerj.11757

Hebert, P. D. N., Ratnasingham, S. y deWaard, J. R. (2003). Barcoding animal life: Cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London B: Biological Sciences, 270 (Supl. 1), S96–S99. https://doi.org/10.1098/rsbl.2003.0025

Hajibabaei, M., Singer, G. A. C., Hebert, P. D. N. y Hickey, D. A. (2007). DNA barcoding: how it complements taxonomy, molecular phylogenetics and population genetics. Trends in Genetics, 23, 167–172. https://doi.org/10.1016/j.tig.2007.02.001

Heindler, F. M., Maes, G. E., Delerue-Ricard, S., Bavière, A. Vanden, Hostens, K. y Volckaert, F. A. M. (2019). Diet composition and gut microbiome of 0-group European plaice Pleuronectes platessa L. - Strong homogeneity and subtle spatial and temporal differences. Journal of Sea Research, 144, 67–77. https://doi.org/10.1016/j.seares.2018.11.004

Hirai, J., Hidaka, K., Nagai, S. y Ichikawa, T. (2017). Molecular-based diet analysis of the early post larvae of Japanese sardine Sardinops melanostictus and Pacific round herring Etrumeus teres. Marine Ecology Progress Series, 564, 99–113. https://doi.org/10.3354/meps12008

Hoenig, B. D, Trevelline, B. K., Nuttle, T. y Porter, B. A. (2021). Dietary DNA metabarcoding reveals seasonal trophic changes among three syntopic freshwater trout species. Freshwater Biology, 66, 509–523. https://doi.org/10.1111/fwb.13656

Hunter, E., Taylor, N., Fox, C. J., Maillard, M., y Taylor, M. I. (2012). Effectiveness of TaqMan probes for detection of fish eggs and larvae in the stomach contents of a teleost predator. Journal of Fish Biology, 81, 320–328. https://doi.org/10.1111/j.1095-8649.2012.03298.x

Ivanova, N., Fazekas, A. J. y Hebert, P. D. N. (2008). Semi-automated, membrane-based protocol for DNA isolation from plants. Plant Molecular Biology Reports, 26, 186–198. https://doi.org/10.1007/s11105-008-0029-4

Jakubaviciute, E., Bergström, U., Eklöf, J. S. Haenel, Q. y Bourlat, S. J. (2017). DNA metabarcoding reveals diverse diet of the three-spinned stickleback in a coastal ecosystem. Plos One, 12, e0186929. https://doi.org/10.1371/journal.pone.0186929

Jedlicka, J. A., Sharma, A. M. y Almeida, R. P. P. (2013). Molecular tools reveal diets of insectivorous birds from predator fecal matter. Conservation Genetics Resources, 5, 879–885. https://doi.org/10.1007/s12686-013-9900-1

Johnson, N. S., Lewandoski, S. A y Merkes, C. (2021). Assessment of sea lamprey (Petromyzon marinus) diet using DNA metabarcoding of feces. Ecological Indicators, 125, 107605. https://doi.org/10.1016/j.ecolind.2021.107605

Juen, A. y Traugott, M. (2006). Amplification facilitators and multiplex PCR: tools to overcome PCR‐inhibition in DNA‐gut‐content analysis of soil‐living invertebrates. Soil Biology y Biochemistry, 38, 1872–1879. https://doi.org/10.1016/j.soilbio.2005.11.034

Jungbluth, M. J., Burns, J., Grimaldo, L., Slaughter, A., Katla, A. y Kimmerer, W. (2021). Feeding habits and novel prey of larval fishes in the northern San Francisco Estuary. Environmental DNA, 3, 1059–1080. https://doi.org/10.1002/edn3.226

Jusino, M. A., Banik, M. T., Palmer, J. M., Wray, A. K., Xiao, L., Pelton, E. et al. (2018). An improved method for utilizing high-through- put amplicon sequencing to determine the diets of insectivorous animals. Molecular Ecology Resources, 19, 176–190. https://doi.org/10.1111/1755-0998.12951

Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M. et al. (2013). Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Research, 41, e1. https://doi.org/10.1093/nar/gks808

Kim, M. J., Kim, H. W., Lee, S. R., Kim, N. Y., Lee, Y. J., Joo, H. T. et al. (2022). Feeding strategy of the wild Korean earhorse (Hippocampus haema). Journal of Marine Science and Engineering, 10, 357. https://doi.org/10.3390/jmse10030357

Kocher, T. D., Thomas, W. K., Meyer, A., Edwards, S. V., Pääbo, S., Villablanca, F. X. et al. (1989). Dynamics of mitochondrial DNA evolution in animals: amplification and sequencing with conserved primers. Proceedings if the National Academy of Sciences of the United States of America, 86, 6196–6200. https://doi.org/10.1073/pnas.86.16.6196

Kodoma, T., Hirai, J., Tamura, S., Takhashi, T., Tanaka, Y., Ishihara, T. et al. (2017). Diet composition and feeding habitats of larval Pacific bluefin tuna Thunnus orientalis in the Sea of Japan: integrated morphological and metagenetic analysis. Marine Ecology Progress Series, 583, 211–226. https://doi.org/10.3354/meps12341

Kume, G., Kobari, T., Hirai, J., Kuroda, H., Takeda, T., Ichinomiya, M. et al. (2021). Diet niche segregation of co-occurring larval stages of mesopelagic and commercially important fishes in the Osumi Strait assessed through morphological, ADN metabarcoding, and stable isotope analyses. Marine Biology, 168, 6.

https://doi.org/10.1007/s00227-020-03810-x

Lazic, T., Corriero, G., Balech, B., Cardone, F., Deflorio, M., Fosso, B. et al. (2021). Evaluating DNA metabarcoding to analyze diet composition of wild long-snouted seahorse Hippocampus guttulatus. En International Workshop on Metrology for the Sea; learning to measure sea health parameters (Metro Sea); IEEE: Reggio Calabria, Italy, 2021; pp. 257–261. https://doi.org/10.1109/MetroSea52177.2021.9611570

Lee, C. I., Wang, F. Y., Liu, M. Y., Chou, T. K. y Liao, T. Y. (2021). DNA metabarcoding for dietary analysis of Holland´s carp (Spinibarbus hollandi) to evaluate the threat to native fishes in Taiwan. Journal of Fish Biology, 99, 1668–1676. https://doi.org/10.1111/jfb.14875

Leray, M., Yang, J. Y., Meyer, C. P., Mills, S. C., Agudelo, N., Ranwez, V. et al. (2013). A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: applications for characterizing coral reef fish gut contents. Frontiers in Zoology, 10, 34. https://doi.org/10.1186/1742-9994-10-34

Leray, M., Meyer, C. P. y Mills, S. C. (2015). Metabarcoding dietary analysis of coral dwelling predatory fish demonstrates the minor contribution of coral mutualists to their highly partitioned, generalist diet. PeerJ, 3, e1047. https://doi.org/10.7717/peerj.1047

Link, S. J. (2002). Ecological consideration in fisheries management: When does it matter? Fisheries, 27, 10–17.

https://doi.org/10.1577/1548-8446(2002)027<0010:ECIFM>2.0.CO;2

Lui, C., Qi, R. J., Jiang, J. Z., Zhang, M. Q. y Wang, J. Y. (2019). Development of a blocking primer to inhibit the PCR amplification of the 18S rDNA sequences of Litipenaeus vannamei and its efficacy in Crassostrea honkongensis. Fronteirs in Microbiology, 10, 830. https://doi.org/10.3389/fmicb.2019.00830

Majaneva, M., Diserud, O. H., Eagle, S. H. C., Hajibabaei, M. y Ekrem, T. (2018). Choice of DNA extraction method affects DNA metabarcoding of unsorted invertebrate bulk samples. Metabarcoding and Metagenomics, 2, e26664. https://doi.org/10.3897/mbmg.2.26664

Malviya, S., Scalco, E., Audic, S., Vincent, F., Veluchamy, A., Poulain, J. et al. (2016). Insights into global diatom distribution and diversity in the world’s ocean. Proceedings of the National Academy of Sciences of the United States of America, 113, E1516-E1525. https://doi.org/10.1073/pnas.1509523113

Matley, J. K. Maes, G. E., Devloo-Delva, F., Huerlimann, R., Chua, G., Tobin, A. J. et al. (2018). Integrating complementary methods to improve diet analysis in fishery-targeted species. Ecology and Evolution, 8, 9503–9515. https://doi.org/10.1002/ece3.4456

Mercado-Salas, N. F., Khodami, S., Kihara, T. C., Elías-Gutiérez, M. y Martínez Arbizu, P. (2018). Genetic structure and distributional patterns of the genus Mastigodiaptomus (Copepoda) in Mexico, with the description of a new species from the Yucatán Peninsula. Arthropod Systematics and Phylogeny, 761, 487–507.

Meyer, M. y Kircher, M. (2010). Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harbor Protocols, 6, pdb.prot5448. https://doi.org/10.1101/pdb.prot5448

Minamoto, T., Yamanaka, H., Takahara, T., Honjo, M. N. y Kawabata, Z. (2012). Surveillance of fish species composition using environmental DNA. Limnology, 13, 193–197. https://doi.org/10.1007/s10201-011-0362-4

Miya, M., Sato, Y., Fukunaga, T., Sado, T., Poulsen, J. Y., Sato, K. et al. (2015). MiFish, a set of universal PCR primers for metabarcoding environmental from fishes: detection of more than 230 subtropical marine species. Royal Society Open Science, 2, 150088. https://doi.org/0.1098/rsos.150088

Miya, M., Gotoh, R. O. y Sado, T. (2020). MiFish metabarcoding: a high-throughput approach for simultaneous detection of multiple fish species from environmental and other samples. Fisheries Science, 86, 1–32. https://doi.org/10.1007/s12562-020-01461-x

Mychek-Londer, J. G., Chaganti, S. R. y Heath, D. D. (2020). Metabarcoding of native and invasive species in stomach contents of Great Lakes fishes. Plos One, 15, e0236077. https://doi.org/10.1371/journal.pone.0236077

Nalley, E. M., Sonahue, M. J. y Toonen, R. J. (2022) Metabarcoding as a tool to examine cryptic algae in the diets of two common grazing surgeonfishes, Acanthurus triostegus and A. nigrofuscus. Environmental DNA, 4, 135–146. https://doi.org/10.1002/edn3.206

Nalley, E. M., Donahue, M. J., Heeman, A. y Toonen, R. J. (2022). Quantifying the diet diversity of herbivorous coral reef fishes using systematic review and DNA metabarcoding. Environmental DNA, 4, 191–205. https://doi.org/10.1002/edn3.247

Novillo, M., Desvignes, T., Moreira, E. y Barrera-Oro, E. (2022). Egg predation in Antarctic fish: the ingestion by Notothenia coriiceps of an entire Trematomus brenacchii spawn identified by molecular techniques. Estuarine, Coastal and Shelf Science, 266, 107742. https://doi.org/10.1016/j.ecss.2022.107742

Oehm, J., Juen, A., Nagiller, K., Neuhauser, S. y Traugott, M. (2011). Molecular scatology: How to improve prey DNA detection success in avian faeces? Molecular Ecology Resources, 11, 620–628. https://doi.org/10.1111/j.1755-0998.2011.03001.x

Oyafuso, Z. S., Toonen, R. J. y Franklin, C. E. (2016). Temporal and spatial trends in prey composition of wahoo Acanthocybium solandri: a diet analysis from the central North Pacific Ocean usin visual and DNA bar-coding techniques. Journal of Fish Biology, 88, 1501–1523. https://doi.org/10.1111/jfb.12928

Palumbi, S. (1996) Nucleic acids II: polymerase chain reaction. En D. Hillis, C. Moritz y B. Mable (Eds.), Molecular systematics, 2nd Ed. (pp. 205-247). Sunderland, Massachusetts: Sinauer Associates, Inc.

Pandey, R. N., Adams, R. P. y Flournoy, L. E. (1996). Inhibition of ran- dom amplified polymorphic DNAs (RAPDs) by plant polysaccharides. Plant Molecular Biology Reporter/ISPMB, 14, 17–22. https://doi.org/10.1007/BF02671898

Panteli, N., Mastoraki, M., Nikouli, E., Lazarina, M., Antonopoulou, E. y Kormas, K. A. (2020). Imprinting statistically sound conclusions for gut microbiota in comparative animal studies: a case study with diet and teleost fishes. Comparative Biochemistry and Physiology-Part D, 36, 100738. https://doi.org/10.1016/j.cbd.2020.100738

Pedraza-Lara, C., Doadrio, I., Breinholt, J. W. y Crandall, K. A. (2012). Phylogeny and evolutionary patterns in the dwarf crayfish subfamily (Decapoda: Cambarellinae). Plos One, 7, e48233. https://doi.org/10.1371/journal.pone.0048233

Piñol, J., San Andrés, V., Clare, E. L., Mir, G. y Symondson, W. O. C. (2014). A pragmatic approach to the analysis of diets of generalist predators: The use of next‐generation sequencing with no blocking probes. Molecular Ecology Resources, 1, 18–26. https://doi.org/10.1111/1755-0998.12156

Piñol, J., Senar, M. A. y Symondson, W. O. C. (2019). The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative. Molecular Ecology, 28, 407-419. https://doi.org/10.1111/mec.14776

Rees, G. N., Shackleton, M. E., Watson, G. O., Dwyer, G. K. y Stoffels, R. J. (2019). Metabarcoding demonstrates dietary niche partitioning in two coexisting blackfish species. Marine and Freshwater Research, 71, 512–517. https://doi.org/10.1071/MF18491

Riaz, T., Shehzad, W., Viari, A., Pompanon, F., Taberlet, P. y Coissac, E. (2011). ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis. Nucleic Acids Research, 39, e145. https://doi.org/10.1093/nar/gkr732

Riccioni, G., Stagioni, M., Piccinetti, C. y Libralato, S. (2018). A metabarcording approach for the feeding habits of European hake in the Adriatic Sea. Ecology and Evolution, 8, 10435–10447. https://doi.org/10.1002/ece3.4500

Rimoldi, S., Torrecillas, S., Montero, D., Gini, E., Makol, A., Valdenegro, V. et al. (2020). Assessment of dietary supplementation with galactomannan oligosaccharides and phytogenics on gut microbiota of European sea bass (Dicentrarchus labrax) fed low fishmeal and fish oil based diet. Plos One, 15, e0231494. https://doi.org/10.1371/journal.pone.0231494

Sambrook, J., Fritsch, E. F. y Maniatis, T. J. (1989). Molecular cloning: a laboratory manual. Cold Spring Harbor, New York: Cold Spring Harbor Laboratory Press.

Sanchez-Peregrin, L. (2017). Study of fish assemblages in Ecklonia radiata dominated rock reefs in subtropical eastern Australia and dietary analyses of three species of generalist predators of the family Labridae (Tesis de maestría). School of Environment, Science and Engineering, Southern Cross University. Lismore, Australia.

Sang, T., Crawford, D. J. y Stuessy, T. F. (1997). Chloroplast DNA phylogeny, reticulate evolution, and biogeography of Paeonia (Paeoniaceae). American Journal of Botany, 84, 1120–1136.

Schrader, C., Schielke, A., Ellerbroek, L. y Johne, R. (2012). PCR inhibitors – occurrence, properties and removal. Journal of Applied Microbiology, 113, 1014-1026. https://doi.org/10.1111/j.1365-2672.2012.05384.x

Sherwood, A. y Presting, G. (2007). Universal primers amplify a 23S rDNA plastid marker in eukaryotic algae and cyanobacteria. Journal of Phycology, 43, 605–608. https://doi.org/10.1111/j.1529-8817.2007.00341.x

Shink, K. G., Sutton, T. M., Murphy, J. M. y López, J. A. (2019). Utilizing DNA metabarcoding to characterize the diet of marine-phase Artic lamprey (Lethenteron camtschaticum) in the eastern Bering Sea. Canadian Journal of Fisheries and Aquatic Sciences, 76, 1993–2002. https://doi.org/10.1139/cjfas-2018-0299

Siegenthaler, A., Wangensteen, O.S., Benvenuto, C., Campos, J. y Mariani, S. (2019). DNA metabarcoding unveils multiscale trophic variation in a widespread coastal opportunist. Molecular Ecology, 28, 232–249. https://doi.org/10.1111/mec.14886

Stamoulis, K. A., Friedlander, A. M., Meywe, C. G., Fernandez-Silva, I. y Toonen, R. J. (2017). Coral reef grazer-benthos dynamics complicated by invasive algae in a small marine reserve. Scientific Reports, 7, 43819. https://doi.org/10.1038/srep43819

Stevens, J. D., Bonfil, R., Dulvy, N. K. y Walker, P. A. (2000). The effects of fishing on sharks, rays, and chimeras (chondrichthyans), and the implications for marine ecosystems. ICES Journal of Marine Science, 57, 476–494. https://doi.org/10.1006/jmsc.2000.0724

Steward, S. D., Kelly, D., Biessy, L., Laroche, O. y Wood, S. A. (2021). Individual diet specialization drives population niche responses to environmental changes in a predator fish population. Food Webs, 27, e00193. https://doi.org/10.1016/j.fooweb.2021.e00193

Su, M., Liu, H., Liang, X., Gui, L. y Zhang, J. (2018). Dietary analysis of marine fish species: enhancing the detection of prey-specific DNA sequences via high-throughput sequencing using blocking primers. Estuaries and Coasts, 41, 560–571. https://doi.org/10.1007/s12237-017-0279-1

Taberlet, P., Coissac, E., Hajibabaei, M. y Rieseberg, L. H. (2012). Environmental DNA. Molecular Ecology, 21, 1789–1793. https://doi.org/10.1111/j.1365-294X.2012.05542.x

Taberlet, P., Bonin, A., Zinger, L. y Coissac, E. (2018). Environmental DNA: for biodiversity research and monitoring. Londres: Oxford University Press. https://doi.org/10.1093/oso/9780198767220.001.0001

Takahashi, M., DiBattista, J. D., Jarman, S., Newman, S. J., Wakefield C. B., Harvey, E. S. et al. (2020). Partitioning of diet between species and life history stages of sympatric and cryptic snappers (Lutjunidae) based on DNA metabarcoding. Scientific Reports, 10, 4319. https://doi.org/10.1038/s41598-020-60779-9

Tate, J. A. y Simpson, B. (2003). Paraphyly of Tarasa (Malvaceae) and diverse origins of the polyploid species. Systematic Botany, 28, 723–737. https://doi.org/10.1043/02-64.1

Tournayre, O., Leuchtmann, M., Filippi-Codaccioni, O., Trillat, M., Piry, S., Pontier, D. et al. (2020). In silico and empirical evaluation of twelve metabarcoding primer set for insectivorous diet analyses. Ecology and Evolution, 10, 6310–6332. https://doi.org/10.1002/ece3.6362

Traugott, M., Thalinger, B., Wallinger, C. y Sint, D. (2021). Fish as predators and prey: DNA-based assessment of their role in food webs. Journal of Fish Biology, 98, 367–382. https://doi.org/10.1111/jfb.14400

Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., Thomsen, P. F. et al. (2016). Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology, 25, 929–942. https://doi.org/10.1111/mec.13428

Vamos, E., Elbrecht, V. y Leese, F. (2017). Short COI markers for freshwater macroinvertebrate metabarcoding. Metabarcoding and Metagenomics, 1, e14625. https://doi.org/10.3897/mbmg.1.14625

Verma, S. K. y Singh, L. (2003). Novel universal primers establish identity of an enormous number of animal species for forensic application. Molecular Ecology Notes, 3, 28–31. https://doi.org/10.1046/j.1471-8286.2003.00340.x

Vesterinen, E. J., Ruokoleinen, L., Wahlberg, N., Peña, C., Roslin, T, Laine, V. N. et al. (2016). What you need is what you eat? Prey selection by the bat Myotis daubentonii. Molecular Ecology, 25, 1581–1594. https://doi.org/10.1111/mec.13564

Vestheim, H. y Jarman, S. N. (2008) Blocking primers to enhance PCR amplification of rare sequences in mixed samples- a case study on prey DNA in Antarctic krill stomach. Frontiers in Zoology, 5, 12. https://doi.org/10.1186/1742-9994-5-12

Villsen, K., Corse, E., Meglécz, E., Archambaud-Suard, G., Vignes, H., Ereskovsky, A. V. et al. (2021). DNA metabarcoding reveals adaptive seasonal variation of individual trophic traits in a critically endangered fish. Molecular Ecology, 31, 5889–5908. https://doi.org/10.1101/2021.01.25.428043

van der Walt, A. J., van Goethem, M. W., Ramond, J. B., Makhalanyane, T. P., Reva, O. y Cowan, D. A. (2017). Assembling metagenomes, one community at a time. BioMed Central Genomics, 18, 521. https://doi.org/10.1186/s12864-017-3918-9

van Zinnicq-Bergmann, M. P. M., Postaire, B. D., Gastrich, K., Heithaus, M. R., Hoopes, I. A., Lyons, K. et al. (2021). Elucidating shark diet with DNA metabarcoding from cloacal swabs. Molecular Ecology Resources, 21, 1056–1067. https://doi.org/10.1111/1755-0998.13315

Wangensteen, O. S., Palacín, C., Guardiola, M. y Turon, X. (2018). DNA metabarcoding of littoral hard-bottom communities: high diversity and database gaps revealed by two molecular markers. PeerJ, 6, e4705. https://doi.org/10.7717/peerj.4705

Waraniak, J. M., March, T. L. y Scribner, K. T. (2019). 18S rRNA metabarcoding diet analysis of a predatory fish community across seasonal changes in prey availability. Ecology and Evolution, 9, 1410–1430. https://doi.org/10.1002/ece3.4857

Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R. y Hebert, P. D. N. (2005). DNA barcoding Australia’s fish species. Philosophical Transactions of the Royal Society B: Biological Sciences, 360, 1847–1857. https://doi.org/10.1098/rstb.2005.1716

White, T. J., Bruns, T., Lee, S. y Taylor, J. (1990). Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. En M. A. Innis, D. H. Gelfrand, J. J. Snisky y J. J. White (Eds.), PCR protocols: a guide to methods and applications (pp. 315–320). San Diego: Academic Press.

Yoo, T. H., Kang, H. E., Lee, S. R., Lee, J. B., Baeck, G. W., Park, H. et al. (2017). Metabarcoding analysis of the stomach contents of the Antarctic Toothfish (Dissostichus mawsoni) collected in the Antarctic Ocean. PeerJ, 5, e3977. https://doi.org/10.7717/peerj.3977

Yu, J., Xue, J. H. y Zhou, S. L. (2011). New universal matK primers for DNA barcoding angiosperms. Journal of Systematics and Evolution, 49, 176–181. https://doi.org/10.1111/j.1759-6831.2011.00134.x

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