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Monitoring of marine nematode communities through 18S rRNA metabarcoding as a sensitive alternative to morphology

Tijdschriftbijdrage - Tijdschriftartikel

Nematodes are suitable indicators for environmental perturbations because their distribution is closely linked to sediment characteristics. To evaluate whether DNA-based approaches can complement or even outperform morphology-based monitoring, careful evaluation of both approaches is needed using field samples that clearly differ in environmental parameters. We compared metabarcoding, targeting the 18S rRNA and COI genes, with morphological identification of the nematode communities in three different land use areas (aquaculture, industry and nature reserve) in Vietnamese mangroves. The areas differed in heavy metal and nitrate content and granulometry. We additionally generated reference Sanger sequences from these areas in order to improve the genus and species level assignments of the metabarcode data. We compared nematode densities, species and genus composition and diversity estimates, and nematode specific indices in relation to the environmental differences between areas. Our results show that multivariate patterns were similar between the three approaches, while the 18S rRNA metabarcoding dataset best described changes in diversity and community composition in relation to the environmental differences in our sites. The taxonomic composition of the samples was strikingly different depending on the method and less taxa were detected using DNA based methods than the morphology-based method. We show that this is mainly attributed to a lack of entries in the reference databases. The 18S rRNA metabarcoding approach provides a reliable and fast way to screen for environmental changes. Nevertheless, when we also want to understand those changes, the ecological and biological information linked to taxonomy remain essential. We therefore advocate that the addition of new reference sequences from vouchered specimens to reference databases should be an essential part of every metabarcoding study.
Tijdschrift: ECOLOGICAL INDICATORS
ISSN: 1470-160X
Volume: 107
Aantal pagina's: 1
Jaar van publicatie:2019