DNA metabarcoding of Neotropical ichthyoplankton: Enabling high accuracy with lower cost

• Autor(a) principal: Nobile, André B.
• Data de Publicação: 2019
• Outros Autores: Freitas-Souza, Diogo, Ruiz-Ruano, Francisco J., Nobile, Maria Lígia MO., Costa, Gabriela O., De Lima, Felipe P., Camacho, Juan Pedro M., Foresti, Fausto, Oliveira, Claudio
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.3897/mbmg.3.35060; http://hdl.handle.net/11449/205143
• topic: DNA Barcoding; Fisheries management; Ichthyofauna; Upper Paraná River

Knowledge of ichthyoplankton dynamics is extremely important for conservation management as it can provide information about preferential spawning sites, reproductive period, migratory routes and recruitment success, which can be used to guide management and conservation efforts. However, identification of the eggs and larvae of Neotropical freshwater fish is a difficult task. DNA barcodes have emerged as an alternative and highly accurate approach for species identification, but DNA barcoding can be time-consuming and costly. To solve this problem, we aimed to develop a simple protocol based on DNA metabarcoding, to investigate whether it is possible to detect and quantify all species present in a pool of organisms. To do this, 230 larvae were cut in half, one half was sequenced by the Sanger technique and the other half was used to compose six arrays with a pool of larvae that were sequenced using a next-generation technique (NGS). The results of the Sanger sequencing allowed the identification of almost all larvae at species level, and the results from NGS showed high accuracy in species detection, ranging from 83% to 100%, with an average of 95% in all samples. No false positives were detected. The frequency of organisms in the two methods was positively correlated (Pearson), with low variation among species. In conclusion, this protocol represents a considerable advance in ichthyoplankton studies, allowing a rapid, cost-effective, quali-quantitative approach that improves the accuracy of identification.