Details:

Journal Title:
Biodiversity Information Science and Standards
Personal Author:
Silliman, Katherine ; Anderson, Sean ; Storo, Rachael ; Thompson, Luke
Silliman, Katherine ; Anderson, Sean ; Storo, Rachael ; Thompson, Luke Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) ; NGI (Northern Gulf Institute)
OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) ; NGI (Northern Gulf Institute) Less -
Description:
Metabarcoding of DNA collected from an environmental sample (eDNA) is increasingly employed in marine biodiversity surveys, with the ability to target taxa from microbes to plankton to large vertebrates depending on the molecular markers used. These techniques are often the only viable method to detect certain taxonomic groups, and therefore provide observations that are currently under-represented on existing biodiversity data platforms, such as the Ocean Biodiversity Information System (OBIS) and the Global Biodiversity Information Facility (GBIF). Some of the reasons for this disconnect include the unique data structures inherent to eDNA datasets, the complexities of combining marine observation data and environmental data (De Pooter et al. 2017), and the minimal availability of documented examples. Here we present a detailed case study on the preparation of marine metabarcoding survey data for publication to OBIS. This data comes from the 2021 Gulf of Mexico Ecosystems and Carbon Cycle (GOMECC) cruise led by the National Oceanic and Atmospheric Administration (NOAA), employing 17 coastal-offshore transects across the Gulf of Mexico and the Atlantic Ocean. Metabarcoding libraries targeted bacteria and archaea with the 16S rRNA marker and eukaryotes with the 18S rRNA marker. Amplicon sequence variants (ASVs) were inferred for each marker, then taxonomy was assigned to these ASVs using the open-sourced reference databases PR2 5.0.1 and SILVA 138.1. OBIS requires that taxonomic assignments are converted to the World Register of Marine Species (WoRMS) nomenclature, which can be particularly challenging for marine bacteria and archaea as these taxa are underrepresented on WoRMS. Three tables—the per-sample ASV observation counts, assigned taxonomy of the ASV sequences, and sample collection data—were then converted to the DNA derived extension for Darwin Core (Abarenkov et al. 2023) using a combination of new and OBIS-provided Python scripts (LaScala-Gruenewald et al. 2021). This workflow is available at the NOAA Omics Data Management Guide*1, which will also host links to NOAA Omics datasets. Some of the key challenges to navigate when preparing metabarcoding data for OBIS include: developing a sample collection data template, converting taxonomic assignments to WoRMS nomenclature while preserving the original assignments, and recording the complex methodological and bioinformatic processes involved in data generation in order to be reproducible. developing a sample collection data template, converting taxonomic assignments to WoRMS nomenclature while preserving the original assignments, and recording the complex methodological and bioinformatic processes involved in data generation in order to be reproducible. We describe our workflow for tackling these challenges, with the aim of fostering discussion on best practices for publishing marine eDNA data to biodiversity data platforms. This work is part of a larger effort across NOAA ’Omics to develop a comprehensive bioinformatics platform and data management framework for marine eDNA and microbiome data.
Keywords:
[+]
General Engineering
Source:
Biodiversity Information Science and Standards, 7
DOI:
https://doi.org/10.3897/biss.7.111048
ISSN:
2535-0897
Publisher:
Pensoft Publishers
Document Type:
Journal Article
Funding:
Grant no. NA21OAR4320190
License:
https://creativecommons.org/licenses/by/4.0/
Rights Information:
CC BY
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:fe78bacd22eee8db198cf8fa3210f2dcf7e97bc99a171dbbec8b518532233291
Download URL:
https://repository.library.noaa.gov/view/noaa/58920/noaa_58920_DS1.pdf
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