Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition
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Author(s)
Romac, Sarah
Alberti, Adriana
Poulain, Julie
Engelen, Stefan
Labadie, Karine
Ferrera, Isabel
Albini, Guillaume
Aury, Jean-Marc
Belser, Caroline
Bertrand, Alexis
Date Issued
August 2017
Journal
Scientific Data
Publisher
Springer Nature
Citation
Alberti, Adriana, Julie Poulain, Stefan Engelen, Karine Labadie, Sarah Romac, Isabel Ferrera, Guillaume Albini, et al. “Viral to Metazoan Marine Plankton Nucleotide Sequences from the Tara Oceans Expedition.” Scientific Data 4 (August 2017): 170093 © 2017 The Author(s)
Version
Final published version
Abstract
A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009-2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world's planktonic ecosystems.
MIT Department
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Terms of Use
Attribution 4.0 International (CC BY 4.0)
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DOI of Published Version
https://doi.org/10.1038/SDATA.2017.93
