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The largest dataset of soil metagenomes has recently been released by the National Ecological Observatory Network (NEON), which performs annual shotgun sequencing of soils at 47 sites across the United States. NEON serves as a valuable educational resource, thanks to its open data and programming tutorials, but there is currently no introductory tutorial for accessing and analyzing the soil shotgun metagenomic dataset. Here, we describe methods for processing raw soil metagenome sequencing reads using a bioinformatics pipeline tailored to the high complexity and diversity of the soil microbiome. We describe the rationale, necessary resources, and implementation of steps such as cleaning raw reads, taxonomic classification, assembly into contigs or genomes, annotation of predicted genes using custom protein databases, and exporting data for downstream analysis. The workflow presented here aims to increase the accessibility of NEON’s shotgun metagenome data, which can provide important clues about soil microbial communities and their ecological roles.
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Characterising Soil Eukaryotic Diversity From NEON Metagenomics Datasets
ABSTRACT Belowground eukaryotic diversity serves a vital role in soil ecosystem functioning, yet the composition, structure, and macroecology of these communities are significantly under‐characterized. The National Ecological Observatory Network (NEON) provides publicly available datasets from long‐term surveillance of numerous taxa and ecosystem properties. However, this dataset is not routinely evaluated for its eukaryotic component, likely because analyzing metagenomes for eukaryotic sequences is hampered by low relative sequence abundance, large genomes, poorer eukaryote representation in public reference databases, and is not yet mainstream. We mined the NEON soil metagenome datasets for 18S rRNA sequences using a custom‐built pipeline and produced a preliminary assessment of biodiversity trends in North American soil eukaryotes. We extracted ~800 18S rRNA reads per sample (~22,000 reads per site) from 1455 samples from 495 plots across 45 NEON sites in 11 biomes, which corresponded to 5183 genera in 35 phyla. To our knowledge, this represents the first large‐scale soil eukaryote analysis of NEON data. We asked whether taxonomic richness paralleled patterns previously established ecological trends and found that eukaryotic richness was negatively correlated with pH, managed sites lowered eukaryotic richness by 47%, most biomes had a distinct eukaryotic community, and fire decreased eukaryotic richness. These findings parallel generally accepted ecological trends and support the notion that NEON soil metagenome datasets can and should be used to explore spatiotemporal patterns in soil eukaryote diversity, its association with ecosystem functioning, and its response to environmental changes in North America.
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- Award ID(s):
- 2217817
- PAR ID:
- 10660646
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- Volume:
- 26
- Issue:
- 1
- ISSN:
- 1755-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1111/1755-0998.70062
