Fungal Community Soil Metabarcoding Data from Four Sequencing Strategies

A dataset comparing fungal community structures derived from soil metabarcoding using four different sequencing technologies. The data was generated by Brendan Furneaux of Uppsala University to investigate methodological challenges in taxonomic and phylogenetic placement. It includes results from short-read Illumina MiSeq, Ion Torrent Ion S5, and PacBio RS II sequencing, as well as long-read PacBio RS II sequencing of full ITS and partial LSU regions.

Use Cases

• Compare community structure and diversity results based on different statistical methods applied to the same sequencing data.
• Benchmark short-read versus long-read amplicon sequencing technologies for fungal metabarcoding.
• Develop or test denoising algorithms for long reads in diverse communities using the described split-and-reconstruct approach.
• Construct phylogenetic trees from long-amplicon metabarcoding reads to facilitate taxonomic identification.
• Evaluate a hybrid sequencing strategy using short amplicons for breadth and long amplicons for local species pool characterization.

Strengths

• Compares four distinct sequencing strategies: Illumina MiSeq, Ion Torrent Ion S5, and two PacBio RS II protocols.
• Includes both short (300-400 bp) and long (1200-1600 bp) amplicon sequencing data, enabling methodological comparison.
• Data supports phylogenetic tree construction from metabarcoding reads, a feature enabled by long-read sequencing.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Brendan Furneaux, Uppsala University

Collection Method

Soil metabarcoding using four sequencing technologies.