ArticlePloS one2020
Taxonomic profiling of individual nematodes isolated from copse soils using deep amplicon sequencing of four distinct regions of the 18S ribosomal RNA gene.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Next-Gen intestinal parasite detection: Leveraging metataxonomics for improved diagnosis of intestinal protists and helminths.PloS one · 2026Article
- Optimization of 18 S rRNA metabarcoding for the simultaneous diagnosis of intestinal parasites.Scientific reports · 2024Article
- Metagenomics and metatranscriptomics as potential driving forces for the exploration of diversity and functions of micro-eukaryotes in soil.3 Biotech · 2023Review
- Handling of targeted amplicon sequencing data focusing on index hopping and demultiplexing using a nested metabarcoding approach in ecology.Scientific reports · 2021Article
- First Evidence That Nematode Communities in Deadwood Are Related to Tree Species Identity and to Co-Occurring Fungi and Prokaryotes.Microorganisms · 2021Article
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- Microbial methods matter: Identifying discrepancies between microbiome denoising pipelines using a leaf biofilm taphonomic dataset.Applications in plant sciencesArticle
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Nematodes are representative soil metazoans with diverged species that play crucial roles in nutrient recycling in the pedosphere. Qualitative and quantitative information on nematode communities is useful for assessing soil quality, and DNA barcode-mediated taxonomic analysis is a powerful tool to investigate taxonomic compositions and changes in nematode communities. Here, we investigated four regions (regions 1-4) of the 18S small subunit ribosomal RNA (SSU) gene as PCR targets of deep amplicon sequencing for the taxonomic profiling of individual soil nematodes. We determined the sequence variants (SVs) of 4 SSU regions for 96 nematodes (total 384 amplicons) isolated from copse soils and assigned their taxonomy using the QIIME2 software with dada2 or deblur algorithm and the SILVA database. Dada2 detected approximately 2-fold more nematode-derived SVs than deblur, and a larger number of SVs were obtained in regions 1 and 4 than those in other regions. These results and sufficient reference sequence coverage in region 4 indicated that DNA barcoding using a primer set for region 4 followed by dada2-based analysis would be most suitable for soil nematode taxonomic analysis. Eighteen SSU-derived operational taxonomic units (rOTUs) were obtained from 68 isolates, and their orders were determined based on the phylogenetic trees built by four regional sequences of rOTUs and 116 nematode reference species as well as the BLASTN search. The majority of the isolates were derived from three major orders Dorylaimida (6 rOTUs, 51.5% in 68 isolates), Rhabditida (4 rOTUs, 29.4%), and Triplonchida (7 rOTUs, 17.6%). The predicted feeding types of the isolates were fungivores (38.2% in total nematodes), plant feeders (32.4%), and 14.7% for both bacterivores and omnivores/predators. Additionally, we attempted to improve the branch structure of phylogenetic trees by using long nucleotide sequences artificially prepared by connecting regional sequences, but the effect was limited.
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