18S rRNA V9 metabarcoding for diet characterization: a critical evaluation with two sympatric zooplanktivorous fish species. Issue 6 (19th February 2016)

• Record Type: Journal Article
• Authors: Albaina, Aitor; Aguirre, Mikel; Abad, David; Santos, María; Estonba, Andone
• Is Part Of: Ecology and evolution. Volume 6:Issue 6(2016:Apr.)
• Page Start: 1809
• Page End: 1824
• Publication Date: 2016-02-19
• Subjects: 18S rRNA V9 -- diet analysis -- metabarcoding -- MiSeq paired‐end technology -- plankton -- Sardina pilchardus -- Sprattus sprattus; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.1986
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: The potential of the 18S rRNA V9 metabarcoding approach for diet assessment was explored using MiSeq paired‐end (PE; 2 × 150 bp) technology. To critically evaluate the method′s performance with degraded/digested DNA, the diets of two zooplanktivorous fish species from the Bay of Biscay, European sardine ( Sardina pilchardus ) and European sprat ( Sprattus sprattus ), were analysed. The taxonomic resolution and quantitative potential of the 18S V9 metabarcoding was first assessed both in silico and with mock and field plankton samples. Our method was capable of discriminating species within the reference database in a reliable way providing there was at least one variable position in the 18S V9 region. Furthermore, it successfully discriminated diet between both fish species, including habitat and diel differences among sardines, overcoming some of the limitations of traditional visual‐based diet analysis methods. The high sensitivity and semi‐quantitative nature of the 18S V9 metabarcoding approach was supported by both visual microscopy and qPCR‐based results. This molecular approach provides an alternative cost and time effective tool for food‐web analysis. Abstract : The potential of 18S rRNA V9 metabarcoding for diet characterization was evaluated with two sympatric zooplanktivorous fish species. The method successfully discriminated diet between both fish species, including habitat and diel differences, overcoming some of the limitations of traditional visual‐based diet analysis methods. The high sensitivity and semiquantitative nature of the 18S V9 metabarcoding approach was supported by both visual microscopy and qPCR‐based results.