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Technique

Inclusion of database outgroups reduces false positives in fungal metabarcoding taxonomic assignments

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Pages 571-577 | Received 06 Dec 2022, Accepted 14 Apr 2023, Published online: 17 May 2023
 

ABSTRACT

Metabarcoding studies of fungal communities rely on curated databases for assigning taxonomy. Any host or other nonfungal environmental sequences that are amplified during polymerase chain reaction (PCR) are inherently assigned taxonomy by these same databases, possibly leading to ambiguous nonfungal amplicons being assigned to fungal taxa. Here, we investigated the effects of including nonfungal outgroups in a fungal taxonomic database to aid in detecting and removing these nontarget amplicons. We processed 15 publicly available fungal metabarcode data sets and discovered that roughly 40% of the reads from these studies were not fungal, although they were assigned as Fungus sp. when using a database without nonfungal outgroups. We discuss implications for metabarcoding studies and recommend assigning taxonomy using a database with outgroups to better detect these nonfungal amplicons.

ACKNOWLEDGMENTS

We would like to especially thank the authors of the original research studies included in this paper. Their commitment to reproducible and open science enabled us to reuse their data to explore our hypotheses.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

DATA AVAILABILITY STATEMENT

All raw sequenced used in this study come from previously published work and are publicly available on the Sequence Read Archive under their listed accessions (). All analysis code is publicly available as a versioned GitHub repository release via Zenodo (Zahn Citation2022).

SUPPLEMENTARY MATERIAL

Supplemental data for this article can be accessed online at https://doi.org/10.1080/00275514.2023.2206931

Additional information

Funding

This work was supported by the Utah Valley University Scholarly Activities Committee.

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