Functional Annotation Workflow for Fungal Transcriptomes

Abstract Although RNA sequencing (RNA-seq) enables rapid transcriptome profiling, functional annotation of fungal transcriptomes remains challenging. Existing tools prioritize broad taxonomic coverage, and reference genomes are scarce for non-model species. This study aimed to develop a fungal-specific functional annotation workflow to support rapid and accurate functional analyses downstream of RNA-seq, independent of reference genome availability. To evaluate the workflow, RNA-seq data from 57 samples of Lentinula edodes strain H600 (shiitake mushroom) were retrieved, along with full-length transcript sequencing (Iso-Seq) data and corresponding RNA-seq data from 20 samples of Phakopsora pachyrhizi (Asian soybean rust) from public databases. The workflow successfully annotated over 96% of protein-coding transcripts and demonstrated applicability to Iso-Seq data. Functional enrichment analyses revealed higher-resolution functional detection than existing annotation tools. Furthermore, integrating homology searches against fungal-specific databases with expression pattern-based annotations highlighted the workflow’s utility for target identification in genome editing and other applications. Overall, the results of this study highlight the potential of the developed workflow in facilitating the discovery of functionally important transcripts and their translation into biotechnological applications. Competing Interest Statement The authors have declared no competing interest. Footnotes d235537{at}hiroshima-u.ac.jp Some Figure citations were missing in the previous version, and those are fixed in this version. Abbreviations - TPM - Transcripts Per Million - RNA-seq - RNA Sequencing - Iso-Seq - Full-Length Transcript Sequencing - NGS - Next-Generation Sequencing - NCBI - National Center for Biotechnology Information - SRA - Sequence Read Archive - PCA - Principal Component Analysis - CV - Coefficient of Variation