metaPR²: a database of eukaryotic 18S rRNA metabarcodes with an emphasis on protists

Abstract

In recent years, metabarcoding has become the method of choice for investigating the composition and assembly of microbial eukaryotic communities, and an increasing number of environmental datasets are being published. Although unprocessed sequence files are often publicly available, processed data, i.e. sequences clustered as operational taxonomic units (OTUs) or amplicon sequence variants (ASVs) are rarely at hand in a comparable format. This hampers comparative studies between different environments and datasets, for example examining the biogeographical patterns of specific groups/species, as well analysing the micro-genetic diversity within these groups. Here, we present a newly-assembled database of processed 18S rRNA metabarcodes that are annotated with the PR2 reference sequence database. This database, called metaPR2, contains 41 datasets corresponding to more than 4,000 samples and 73,000 ASVs. The database is accessible through both a web-based interface (https://shiny.metapr2.org) and as an R package, and should prove very useful to all researchers working on protist diversity in a variety of systems.

Arctic phytoplankton spring bloom diversity across the marginal ice zone in Baffin Bay

“…Indicator species analysis ( indicspecies package, De Cáceres et al 2010) was performed with abundant taxa (selected as described above) within each size fraction in order to find significant association between taxa and a given sector (or combination of sectors), using the default IndVal index as statistic test and 9999 random permutations. Global distribution of ASVs was performed using the metaPR 2 database (https://shiny.metapr2.org, Vaulot et al 2022) which contains metabarcodes from 41 public datasets representing more than 4,000 samples distributed over a wide range of ecosystems. ASV sequences from the present study were entered in the “Query” panel, and matching metaPR 2 ASVs (100% similarity) were displayed in the “Map” panel.…”

Diversity and biogeography of planktonic diatoms in Svalbard fjords: The role of dispersal and Arctic endemism in phytoplankton community structuring

“…For biogeographic analysis, we used a compilation of published metabarcoding datasets from different surveys that employed environmental metabarcoding targeting the V4 region of the 18S rRNA gene. The compiled dataset (metaPR 2 ; Vaulot et al, 2022) has global coverage of coastal areas as it includes the samples from the Ocean Sampling Day survey (Kopf et al, 2015), notably in the northern hemisphere, as well as several oceanic transects based on the metabarcoding data collected within, e.g. the Tara…”

“…Metadata and sequence processing are detailed in Vaulot et al (2022). In brief, raw sequence files and metadata were downloaded from NCBI SRA web site (https://www.…”

Beyond the limits of the unassigned protist microbiome: inferring large-scale spatio-temporal patterns of marine parasites

“…Here we have explored both biogeographical and temporal patterns of protists at the species level without requiring a reference taxonomic match. Our FAIR (Findable, Accessible, Interoperable and Reusable) computational workflow that allows to integrate data from heterogeneous ecosystem sampling protocols, such as coastal time-series and open sea campaigns and can be applied to any targeted protist group of any metabarcoding dataset, of the same marker gene, for example originating from the metaPR2 database [54] and Ocean Barcode Atlas [55]. The taxa identified by the network could then be specifically targeted for in situ hybridisation [43] and isolation for single-cell omics [31].…”