FN Archimer Export Format PT J TI Evaluating sediment and water sampling methods for the estimation of deep-sea biodiversity using environmental DNA BT AF Brandt, Miriam Pradillon, Florence Trouche, Blandine Henry, Nicolas Liautard-Haag, Cathy Cambon-Bonavita, Marie-Anne Cueff-Gauchard, Valerie Wincker, Patrick Belser, Caroline Poulain, Julie Arnaud-Haond, Sophie Zeppilli, Daniela AS 1:1;2:2;3:6;4:4;5:7;6:3;7:3;8:5;9:5;10:5;11:1;12:2; FF 1:PDG-RBE-MARBEC-LHM;2:PDG-REM-EEP-LEP;3:;4:;5:;6:PDG-REM-EEP-LMEE;7:PDG-REM-EEP-LMEE;8:;9:;10:;11:PDG-RBE-MARBEC-LHM;12:PDG-REM-EEP-LEP; C1 MARBEC, IFREMER, IRD, CNRS, Univ Montpellier, Sète, France Centre Brest, Laboratoire Environnement Profond (REM/EEP/LEP), IFREMER, CS10070, 29280, Plouzané, France IFREMER, CNRS, Laboratoire de Microbiologie Des Environnements Extrêmes (LM2E), Univ Brest, Plouzané, France CNRS, Station Biologique de Roscoff, AD2M, UMR 7144, Sorbonne University, 29680, Roscoff, France Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ of Évry, Paris-Saclay University, 91057, Evry, France IFREMER, CNRS, Laboratoire de Microbiologie Des Environnements Extrêmes (LM2E), Univ Brest, Plouzané, France MARBEC, IFREMER, IRD, CNRS, Univ Montpellier, Sète, France C2 IFREMER, FRANCE IFREMER, FRANCE IFREMER, FRANCE CNRS, FRANCE GENOMIQUE METABOLIQUE, FRANCE UBO, FRANCE UNIV MONTPELLIER, FRANCE SI SETE BREST SE PDG-RBE-MARBEC-LHM PDG-REM-EEP-LEP PDG-REM-EEP-LMEE UM BEEP-LM2E MARBEC IN WOS Ifremer UPR WOS Ifremer UMR WOS Cotutelle UMR DOAJ copubli-france copubli-univ-france IF 4.997 TC 13 UR https://archimer.ifremer.fr/doc/00689/80094/83149.pdf https://archimer.ifremer.fr/doc/00689/80094/83150.pdf https://archimer.ifremer.fr/doc/00689/80094/83151.xlsx https://archimer.ifremer.fr/doc/00689/80094/83152.xlsx LA English DT Article CR AMIGO ESSNAUT 2016 BO L'Atalante AB Despite representing one of the largest biomes on earth, biodiversity of the deep seafloor is still poorly known. Environmental DNA metabarcoding offers prospects for fast inventories and surveys, yet requires standardized sampling approaches and careful choice of environmental substrate. Here, we aimed to optimize the genetic assessment of prokaryote (16S), protistan (18S V4), and metazoan (18S V1–V2, COI) communities, by evaluating sampling strategies for sediment and aboveground water, deployed simultaneously at one deep-sea site. For sediment, while size-class sorting through sieving had no significant effect on total detected alpha diversity and resolved similar taxonomic compositions at the phylum level for all markers studied, it effectively increased the detection of meiofauna phyla. For water, large volumes obtained from an in situ pump (~ 6000 L) detected significantly more metazoan diversity than 7.5 L collected in sampling boxes. However, the pump being limited by larger mesh sizes (> 20 µm), only captured a fraction of microbial diversity, while sampling boxes allowed access to the pico- and nanoplankton. More importantly, communities characterized by aboveground water samples significantly differed from those characterized by sediment, whatever volume used, and both sample types only shared between 3 and 8% of molecular units. Together, these results underline that sediment sieving may be recommended when targeting metazoans, and aboveground water does not represent an alternative to sediment sampling for inventories of benthic diversity. PY 2021 PD APR SO Scientific Reports SN 2045-2322 PU Springer Science and Business Media LLC VL 11 IS 1 UT 000640428900004 DI 10.1038/s41598-021-86396-8 ID 80094 ER EF