Among them, speed, cost per sample, coverage, independence of taxonomic expertise, and ability to detect unsampled species that leave DNA in the environment ( Rees et al., 2014). Although several technical and methodological challenges remain, such as those related to contamination, primer biases, sequencing artefacts, delineation of taxonomic units, or databases’ depth ( Thomsen & Willerslev, 2015 Carugati et al., 2015 Pawlowski, Lejzerowicz & Esling, 2014a Leray & Knowlton, 2016 Wangensteen & Turon, 2016), metabarcoding has important advantages relative to morphology-based studies. The detection of biodiversity using genetic tags obtained from eDNA (metabarcoding, Taberlet et al., 2012a) provides a fast and reliable method for monitoring biodiversity ( Ji et al., 2013 Dafforn et al., 2014 Leray & Knowlton, 2016). The era of eDNA was initiated in prokaryote microbiology (e.g., Sogin et al., 2006 Roesch et al., 2007) and subsequently expanded to the study of eukaryote diversity, of both micro- and macro-organisms (e.g., Bik et al., 2012a Fonseca et al., 2014 Leray & Knowlton, 2015 Leray & Knowlton, 2016 Thomsen & Willerslev, 2015 Brannock & Halanych, 2015 Brannock et al., 2016). The use of environmental DNA (eDNA) is revolutionizing the way we assess biodiversity and has the potential to change practices and policies in management and conservation ( Bohmann et al., 2014 Kelly et al., 2014 Handley, 2015 Creer et al., 2016). We provide metabarcoding protocols and guidelines for biomonitoring of these key communities in order to generate information applicable to management efforts. Both datasets showed overall similar spatial trends, but most groups had higher MOTU richness with the DNA template, while others, such as nematodes, were more diverse in the RNA dataset. We compared the information obtained from metabarcoding DNA and RNA and found more total MOTUs and more MOTUs per sample with DNA (ca. We found a marked heterogeneity at all scales, with important differences between layers of sediment and significant changes in community composition with zone (canyon vs slope), depth, and season. Among metazoans, Nematoda, Arthropoda and Annelida were the most diverse. We found a total of 5,569 molecular operational taxonomic units (MOTUs), dominated by Metazoa, Alveolata and Rhizaria. Our study was performed in a submarine canyon and its adjacent slope in the Northwestern Mediterranean Sea, sampled along a depth gradient at two different seasons. We chose a recently developed eukaryotic marker based on the v7 region of the 18S rRNA gene.
We assessed spatio-temporal patterns of diversity in deep-sea sediment communities using metabarcoding. Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA. Cite this article Guardiola M, Wangensteen OS, Taberlet P, Coissac E, Uriz MJ, Turon X. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. Licence This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. 4 Laboratoire d’Ecologie Alpine (LECA), Centre National de la Recherche Scientifique and Université Grenoble-Alpes, Grenoble, France DOI 10.7717/peerj.2807 Published Accepted Received Academic Editor Sarah Samadi Subject Areas Biodiversity, Ecology, Genomics, Marine Biology, Zoology Keywords Sediments, eDNA, 18S, eRNA, Meiofauna, Submarine canyons, Biomonitoring Copyright © 2016 Guardiola et al.
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