Cho, Yoonhee
- Department of Forest Bioeconomy and Technology, Swedish University of Agricultural Sciences
- Seoul National University
Abstract
Next-generation sequencing (NGS) has become a powerful and efficient tool for surveying mycorrhizal mycobiome diversity, surpassing classical methods in accuracy and throughput. Long-read NGS techniques are increasingly applied under the assumption that they provide better taxonomic resolution, yet their use often lacks a balanced evaluation against the established strengths and limitations of widely used short-read NGS technologies. This study compares Illumina MiSeq and PacBio Sequel platforms in analyzing the mycorrhizal mycobiome of Pinus densiflora roots, focusing on how sequencing platforms and database choice influence taxonomic resolution and diversity patterns. Both platforms detected mycorrhizal taxa with similar taxonomic resolution, recovering nearly all taxa previously reported from pine roots. Most mycorrhizal taxa were shared between datasets, although several taxa were detected exclusively by one platform. In terms of diversity, the short-read dataset showed higher diversity due to greater sequencing depth, whereas the long-read dataset offered improved identification of rare or closely related taxa owing to longer sequence information. Moreover, supplementing reference databases with locally derived sequences enhanced taxonomic resolution and the detection of native taxa in both approaches, with a stronger effect for the long-read dataset. Overall, our results emphasize that short- and long-read sequencing each have distinct advantages for mycorrhizal community analysis, and that the use of curated local reference databases is essential to maximize taxonomic resolution and improve the detection of regionally unique taxa.
Keywords
mycorrhizal fungi; mycobiome; Pinus densiflora; Illumina MiSeq; PacBio Sequel
Published in
Journal of microbiology
2026, volume: 64, number: 1, article number: e2509008
Publisher: MICROBIOLOGICAL SOCIETY KOREA
SLU Authors
UKÄ Subject classification
Microbiology
Publication identifier
- DOI: https://doi.org/10.71150/jm.2509008
Permanent link to this page (URI)
https://res.slu.se/id/publ/146275