GloSED - Global standardised soil eukaryome dataset

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Authors: Mikryukov, Vladimir, Global Soil Mycobiome consortium (GSMc), Tedersoo, Leho
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Abstract

Global Standardised Soil Eukaryome Dataset (GloSED) Dataset description The GloSED dataset is a metabarcoding-based dataset encompassing the entire spectrum of soil eukaryotes collected and analysed using standardized protocols. Key characteristics - Sampling sites: 4,147 globally distributed locations across 121 countries - Taxonomic scope: Complete soil eukaryome including fungi, protists, animals, and plants - Operational taxonomic units: 988,824 curated OTUs - Sequencing technology: PacBio long-read sequencing of full-length ITS Data collection and processing - Standardized sampling design: 50x50 m plots - Soil cores: 40 cores per plot (5 cm diameter x 5 cm depth), pooled by volume - DNA extraction: PowerMax Soil DNA Isolation kit (Qiagen) with FavorPrep cleanup - Primers: universal eukaryotic primers ITS9mun/ITS4ngsUni - Processing: NextITS v.1.0.0 workflow (DOI: 10.5281/zenodo.15074882) - Taxonomic annotation: EUKARYOME v.1.9.4 database (DOI: 10.1093/database/baae043) Data files and formats Core data - `GloSED__OTU_sequences.fasta.gz`: Quality-filtered representative sequences for all OTUs, FASTA format - `GloSED__OTU_table.tsv.zip`: Sample-by-OTU abundance matrix (TSV format) - `GloSED__Taxonomy.tsv.zip`: Complete taxonomic annotations with UNITE-based species hypotheses (TSV format) - `GloSED__OTU_table.parquet`: Columnar format of abundance data for efficient querying (Parquet format) - `GloSED__Taxonomy.parquet`: Columnar format of taxonomic data (Parquet format) - `GloSED__phyloseq.RData`: phyloseq object for R-based analyses - `GloSED__BIOM.biom`: BIOM v.2.1 format compatible with QIIME2 Metadata files - `GloSED__Sample_metadata.xlsx`: Sample metadata - `DRI.json`: Data Reuse Information tag with ORCID identifiers - `DRI.csv`: Tabular format mapping accession IDs - `Contributors.xlsx`: List of contributors Usage notes To load the phyloseq object in R, use the following command: library(phyloseq)physeq

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 March 2026
Language
EN
Document type
Dataset