Stage-specific RNA regulomes of Trichophyton mentagrophytes: mRNA-lncRNA-miRNA interplay in spore-hypha transition

1 Stage-specific RNA regulomes of Trichophyton mentagrophytes: mRNA-lncRNA-miRNA interplay in spore-hypha transition Wudian Xiao1* , Zhaodan Wu2*, Jia Zhang1*, Jun Wan1, Ruihuan Zhang1, Xinyi Xiang1, Yang Yu1, Lu Fu1, Kui Yang3, Yang Chen4, Ziyao Xiao1, Ziyu Wang1, Lvqin He1, Jingcan You1, Chunxiang Zhang1 1 BasicMedicineResearchInnovationCenterforcardiometabolicdiseases,MinistryofEducation,DepartmentofCardiology,TheAffiliatedHospitalofSouthwest Medical University, Key Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research, Nucleic Acid Medicine of Luzhou KeyLaboratory,ModelAnimalandHumanDiseaseResearchofLuzhouKeyLaboratory,LaboratoryAnimalCenter,SchoolofBasicMedicalSciences,Schoolof ClinicalMedicine,SchoolofPublicHealth,SouthwestMedicalUniversity,Luzhou,646000,China 2 DepartmentofOrthodontics,StateKeyLaboratoryofOralDiseases,NationalClinicalResearchCenterforOralDiseases,WestChinaHospitalofStomatology, SichuanUniversity,Chengdu,China 3 CollegeofIntelligentManufacturing,ChangchunSci-TechUniversity,Changchun,130600,China 4 DepartmentofRespiratoryandCriticalCareMedicine,LuzhouPeople'sHospital,Luzhou,China Correspondingauthors:WudianXiao([email protected]);LvqinHe([email protected]); JingcanYou([email protected]);ChunxiangZhang([email protected]) Copyright: © Wudian Xiao et al. This is an open access article distributed under terms of the Creative Commons Attribution License (Attribution 4.0 International – CC BY 4.0). Research Article Abstract Background: As a globally distributed dermatophyte, Trichophyton mentagrophytes (T. mentagrophytes) causes diverse dermatophytoses in humans and animals. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), which serve as critical regulators of diverse biological processes, have been extensively characterized in numerous fungal species. However, the role of mRNAs, lncRNAs, and miRNAs during T. mentagrophytes germination remains unexplored. Objectives: In this study, the molecular mechanisms involved in the germination of T. mentagrophytes were systematically investigated. Methods: RNA-sequencing technology, small RNA-sequencing technology, related bioinformatics methods, and qRT-PCR were used to systematically characterize the expression profiles of mRNAs, miRNAs, and lncRNAs in T. mentagrophytes spores and hyphae, and analyze the regulatory mechanisms of mRNAs, miRNAs, and lncRNAs during T. mentagrophytes germination. Results: In our study, RNA-sequencing was performed to identify mRNAs, lncRNAs, and miRNAs in spores and hyphae of T. mentagrophytes. A total of 3,193 differentially expressed mRNAs, 409 differentially expressed lncRNAs, and 119 differentially expressed miRNAs were identified, with qRT-PCR subsequently used to verify the dependability of the sequencing data. In addition, an mRNA-lncRNA-miRNA regulatory network containing 2,672 mRNAs, 107 miRNAs, and 329 lncRNAs was constructed. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis suggested that mRNAs, lncRNAs, and miRNAs may play important roles during spore germination, potentially participating in fundamental biosynthetic, cell wall remodelling, cell cycle regulation, cytoskeletal reorganization, epigenetic regulation, and metabolic processes. Academic editor: Adéla Wennrich Received: 27 July 2025 Accepted: 6 October 2025 Published: 5 November 2025 Citation: Xiao W, Wu Z, Zhang J, Wan J, Zhang R, Xiang X, Yu Y, Fu L, Yang K, Chen Y, Xiao Z, Wang Z, He L, You J, Zhang C (2025) Stage-specific RNA regulomes of Trichophyton mentagrophytes: mRNA-lncRNA-miRNA interplay in spore-hypha transition. IMA Fungus 16: e166433. https://doi.org/10.3897/ imafungus.16.166433 IMA Fungus 16: e166433 (2025) DOI: 10.3897/imafungus.16.166433 * These authors contributed equally to this work. 2 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Conclusion: Our study revealed the characteristics of mRNAs, lncRNAs, and miRNAs in T. mentagrophytes using transcriptomic methods, and set the stage for future pathogenicity studies and antifungal drug development for T. mentagrophytes. Key words: Hyphae, lncRNAs, miRNAs, mRNAs, RNA-sequencing, Spores, Trichophyton mentagrophytes Introduction Trichophyton mentagrophytes (T. mentagrophytes) is a globally distributed zoonotic dermatophyte that infects keratinized tissues (skin, nails, hair follicles), causing persistent dermatophytoses in humans and diverse mammalian hosts. Clinical manifestations include tinea manuum, onychomycosis, tinea capitis, and tinea pedis (Weitzman and Summerbell 1995; Chermette et al. 2008). The recalcitrance of these infections characterized by high recurrence rates and escalating antifungal resistance due to therapeutic overuse, establishes T. mentagrophytes as a critical public health threat (Ebert et al. 2020). The spore-to-hypha transition constitutes a pivotal virulence determinant. During germination, spores adhere to the stratum corneum via extracellular ligands, develop germ tubes, and secrete keratinolytic enzymes (keratinases, lipases, phospholipases) that facilitate tissue invasion (Duek et al. 2004; Elavarashi et al. 2017). Notably, while scanning electron microscopy has delineated morphological events, the transcriptomic regulatory architecture—particularly dynamic interactions among mRNAs, lncRNAs, and miRNAs, remains unexplored in T. mentagrophytes (Duek et al. 2004). Advancements in RNA sequencing (RNA-seq) enable genome-scale profiling of transcriptional networks (Hrdlickova et al. 2017), as demonstrated by antifungal target identification in Trichophyton rubrum (Galvão-Rocha et al. 2023). Non-coding RNAs that are transcribed from non-coding regions of the genome, orchestrate key fungal adaptations. Long non-coding RNAs (lncRNAs; >200 nt) modulate cell wall biogenesis, transcriptional regulation (e.g., GAL-mediated R-loop formation in yeast), and stress responses (Cloutier et al. 2016; Hombach and Kretz 2016; Novačić et al. 2020; Shuman 2020). MicroRNAs (miRNAs; 19–25 nt) guide RNA-induced silencing complexes (RISCs) to target mRNAs via 3’/5’ UTR binding, post-transcriptionally regulating developmental transitions (Iwakawa and Tomari 2022), as evidenced by stage-specific miRNAs in Trichophyton rubrum and iron adaptation in Paracoccidioides brasiliensis (Wang et al. 2018; de Curcio et al. 2021). Despite documented roles of lncRNAs and miRNAs in fungal morphogenesis, no integrated analysis of the tripartite RNA regulome (mRNA-lncRNA-miRNA) exists for T. mentagrophytes germination (Lau et al. 2020; Lai et al. 2023). Recently, we reported a transcriptome analysis of circRNAs in T. mentagrophytes during spore germination (Zhang et al. 2023). That work provided the first insights into RNA-based regulation of fungal morphogenesis in dermatophytes, but was inherently restricted to a single class of non-coding RNAs. To achieve a more comprehensive understanding, the present study integrates expression profiles of mRNAs, lncRNAs, and miRNAs into a unified regulatory framework. This integrated approach allows us to not only catalogue diverse 3 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae RNA species but also to construct candidate competing endogenous RNA (ceRNA) networks, thereby exploring the multilayered control underlying the critical spore-to-hypha transition. Materials and methods Fungal culture and sample collection The T. mentagrophytes wild-type strain ATCC MYA-4439 was provided by BeNa Culture Collection (BNCC, Beijing, China). T. mentagrophytes strain was cultured and maintained on potato dextrose agar medium (BD, Sparks, MD, USA) for 14 days at 28 °C to harvest spores (Wang et al. 2022; Zang et al. 2024). Spores on the mycelium surface were rinsed using 5 mL of sterile distilled water and passed sequentially through three cell filters with pore sizes of 0.05 mm, 0.026 mm, and 0.01 mm (Zhang et al. 2023). In order to collect hyphae, spores were cultured and maintained in yeast extract peptone dextrose medium solution shaken on a THZ-300 shaker (Yiheng Scientific Instrument Co., Shanghai, China) at 200 rpm for 5 days at 28 °C. The hyphae were then filtered through gauze, followed by washing with sterile distilled water to collect pure hyphae. Germination analysis of T. mentagrophytes spores For germination analysis, 20 mL of 1 × 105 spores/mL T. mentagrophytes spore suspension was inoculated into each of a series of 250 mL erlenmeyer flasks containing 80–100 mL of yeast extract peptone dextrose medium, and immediately incubated at 28 °C with constant shaking (200 rpm) (Yiheng Scientific Instrument Co., Shanghai, China). Samples at the time-points 0, 6, 12, and 18 hr post-inoculation were taken directly from the medium and subjected to morphological observation using a motic AE2000 microscope (Motic, Fujian, China). mRNA-lncRNA isolation, ribosomal RNA-depleted strand-specific library construction, and sequencing After total RNA was extracted from the three spore (S, n = 3) and hyphae (H, n = 3) samples using TRIzol® reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions, ribosomal RNA was removed to retain both coding and non-coding RNAs. The remaining RNA was enriched using SPRI beads, fragmented at high temperature, and reverse-transcribed into double-stranded cDNA. The cDNA was then end-repaired, A-tailed, and ligated to adapters, followed by PCR amplification. Amplified products were purified with VAHTS DNA Clean Beads and sequenced on an Illumina NovaSeq X Plus by Gene Denovo Biotechnology Co. (Guangzhou, China). miRNA isolation, library construction, and sequencing Total RNA of spores (S, n = 3) and hyphae (H, n = 3) was extracted with the TRIzol® reagent, followed by enrichment of RNA molecules in the 18–30nt size range by polyacrylamide gel electrophoresis (PAGE). The library construction involved sequential ligation of adapters. After the 3’ adapters were ligated, a 4 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae size-selection step was performed to enrich RNAs between 36–44 nucleotides. The 5’ adapters were then ligated to these size-selected molecules. The ligation products were then reverse transcribed by PCR amplification, and the 140–160 bp size PCR products were enriched to generate a cDNA library and sequenced using Illumina NovaSeq X Plus by Gene Denovo Biotechnology Co. (Guangzhou, China). Analysis of differentially expressed mRNA Initially, low-quality reads were filtered from the raw data using fastp (version 0.18.0) to obtain high-quality clean reads (Chen et al. 2018). Reads mapped to the ribosome database were then removed using Bowtie2 (version 2.2.8) (Langmead and Salzberg 2012). Paired-end clean reads were mapped to the T. mentagrophytes genome (GSA: CRA028745) using HISAT2 (version 2.2.1), and transcripts were reconstructed using Stringtie (version 2.2.3) (Trapnell et al. 2010; Kim et al. 2015; Pertea et al. 2015). All of the reconstructed transcripts were aligned to reference genome and were divided into twelve categories by using gffcompare. We defined transcripts with one of the class codes ‘u, i, j, x, c, e or o’ as novel transcripts. We used the following parameters to identify reliable novel genes: transcripts longer than 200 bp, and had to have more than two exons. A FPKM (fragment per kilobase of transcript per million mapped reads) value was calculated using the RSEM software primarily for assessing gene expression levels and facilitating sample comparisons (Li and Dewey 2011). Correlation analysis was conducted using R to assess the reliability and operational stability of the experimental replicates. The correlation coefficient between two samples was calculated, with values closer to 1 indicating stronger reproducibility. Principal component analysis (PCA) was performed using the R package gmodels (http://www.rproject.org/) to reveal relationships between samples. To ensure analytical rigor, differential expression analysis was performed using DESeq2, which utilizes raw read counts and employs a negative binomial model to identify significantly differentially expressed genes (Love et al. 2014). Genes with a false discovery rate (FDR) < 0.05 and a fold change > 2 were considered differentially expressed. Identification and analysis of lncRNAs All reconstructed transcripts were mapped to the T. mentagrophytes genome and classified into twelve categories using Cuffcompare before selecting transcripts longer than 200 bp and with an exon number greater than two. By requiring more than one exon, our pipeline systematically excludes single-exon lncRNAs. The protein coding potential of the new transcripts was assessed with CNCI (version 2), CPC (version 0.9-r2) and FEELNC (version v0.2) using the default parameters (Kong et al. 2007; Sun et al. 2013; Wucher et al. 2017). Transcripts consistently predicted as non-protein-coding by all three tools were classified as lncRNAs. Potential lncRNAs were classified into five categories based on their position with respect to protein coding genes: intergenic lncRNAs, bidirectional lncRNAs, intronic lncRNAs, antisense lncRNAs, and sense-overlapping lncRNAs. The lncRNA target mRNAs were identified by performing antisense, transand cis-regulation lncRNA analyses with RNAplex 5 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae (version 0.2) (Tafer and Hofacker 2008). The FPKM values, correlation coefficients, PCA, and differentially expressed lncRNAs were assessed as for mRNA (see section 2.5 above). miRNA identification and analysis Reads containing more than one low quality (Q-value ≤ 20) base or unknown nucleotides (N), reads without 3’ adapters, reads containing 5’ adapters, reads containing 3’ and 5’ adapters but no small RNA fragment between them, reads containing poly (A) in the small RNA fragment, and reads shorter than 18 nt (not including adapters) were removed from the raw data. The resulting clean tags were aligned to the GenBank database (Release 209.0) and Rfam database (Release 14.10) to remove rRNA, scRNA, snoRNA, snRNA and tRNA. All clean tags were also aligned to the reference genome (GSA: CRA028745) to remove fragments and repetitive sequences that mapped to exons or introns. Clean tags were aligned to the fungal miRBase database (Release 22) to identify known miRNAs using Bowtie (version 1.1.2). Subsequently, the remaining unaligned tags were compared against miRNA sequences from other species within miRBase, applying a filter that required alignment to precursor sequences while excluding matches beyond the 2 bp extensions of the mature miRNA. The novel miRNA candidates were identified by mirDeep2 based on their genome positions and predicted hairpin structures, after excluding all tags matching known miRNAs, miRNA editing variants, mRNA degradation fragments, repetitive regions, and other non-coding RNAs (including rRNA, scRNA, snoRNA, snRNA, and tRNA) (Mackowiak 2011). miRNA target mRNAs were identified by patmatch (Version 1.2). The transcripts per million (TPM) value was calculated with the following formula: TPM = Actual miRNA counts/Total counts of clean tags × 106. Correlation coefficients and PCA were assessed as for mRNA (see section 2.5 above). We identified miRNAs with a fold change > 2 and P < 0.05 in a comparison as significant differentially expressed miRNAs. Enrichment analysis Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on differentially expressed mRNAs, lncRNAs target mRNAs, miRNAs target mRNAs and ceRNA target mRNAs. For GO enrichment analysis, all differentially expressed genes (DEGs) were mapped to GO terms (http://www.geneontology.org/). The number of genes associated with each term was calculated. GO terms that were significantly enriched in the DEGs compared to the expressed gene universe were identified using a hypergeometric test. Pathway enrichment analysis identified significantly enriched metabolic pathways or signal transduction pathways in DEGs comparing with the expressed gene universe as background gene sets. GO terms and KEGG pathways with FDR ≤ 0.05 were considered significantly enriched. Subsequently, GO enrichment analysis and KEGG pathway analysis were performed on a set of genes by using the Gene Set Enrichment Analysis (GSEA) (Subramanian et al. 2005). Gene sets with |NES| > 1, NOM p-val < 0.05, and FDR q-val < 0.25 were considered differentially expressed. 6 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Orthology-inferred Protein-Protein interaction (PPI) PPI analysis was performed using the STRING v10 database and visualized in Cytoscape (v3.7.1) (Szklarczyk et al. 2015). Since STRING does not contain specific PPI data for T. mentagrophytes, an orthology-based approach was employed. Protein sequences of T. mentagrophytes were mapped to the Saccharomyces cerevisiae reference proteome using reciprocal best BLAST hit orthology inference. The resulting orthology-inferred PPI network was analyzed to identify putative functional modules and hub proteins. Putative hub genes were identified by intersecting the top-ranked candidates from the cytoHubba plugin (evaluated by Degree, Edge Percolated Component (EPC), Eccentricity, and Maximum Neighborhood Component algorithms (MNC)) with key modules derived from Molecular Complex Detection (MCODE) analysis in Cytoscape. The resulting protein-protein interaction network was constructed based on these high-confidence hub genes (Shannon et al. 2003). Construction and analysis of candidate lncRNA – miRNA – mRNA network (ceRNA) CeRNA refers to the pool of transcripts (such as mRNA and lncRNA) that can competitively sequester miRNA activity. Based on the same miRNA response elements (MREs), candidate ceRNA networks between lncRNAs, mRNAs, and miRNA were constructed by assembling differentially expressed mRNAs, lncRNAs and miRNAs. Depending on differentially expressed mRNAs, lncRNAs, and miRNAs, expression correlation between mRNA-miRNA or lncRNA-miRNA with a Spearman Rank correlation coefficient (SCC) ≤ -0.7 were identified as negatively co-expressed lncRNA-miRNA pairs or mRNA-miRNA pairs. Expression correlation between lncRNA-mRNA with a Pearson correlation coefficient (PCC) > 0.9 were selected as co-expressed lncRNA-mRNA pairs. The potential lncRNA-mRNA-miRNA pairs with p-values less than 0.05 (without multiple-testing correction) in the above analysis were screened by the hypergeometric distribution test to obtain the final ceRNA pairs. All co-expressed competing triplets were then assembled to construct ceRNA and visualized with Cytoscape software (v3.6.0). The number of co-expressed targeted miRNAs was defined as the RNA connectivity to identify hub genes. qRT-PCR validation To validate the RNA-seq results, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted for four randomly selected differentially expressed mRNAs, four differentially expressed lncRNAs, and six differentially expressed miRNAs. Total RNA was extracted from spores and hyphae, followed by reverse transcription to cDNA with ReverRra Ace qPCR RT Master Mix (Toyobo, Osaka, Japan). Next, qRT-PCR was conducted with PowerUpTM SYBRTM Green Master Mix (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA). Briefly, the reaction volume contained 5 μL of SYBR Green Master Mix, 1 μL of 10 μM forward and reverse primers, 1 μL of template cDNA, and 3 μL of dH2O in a final volume of 10 μL. The reactions were performed on a QuantStudio 5 PCR System (Applied Biosystems, Thermo Fisher Scientific) as follows: 50 °C for 7 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae 2 min and 95 °C for 2 min, followed by 40 cycles of 95 °C for 1 s and 60 °C for 30 s. A melt curve analysis was performed at 95 °C for 1 s, 60 °C for 20 s, and 95 °C for 1 s. No-template controls and no-reverse transcription controls were included in every qPCR run to monitor contamination. None of these controls showed specific amplification, confirming the specificity and reliability of the experimental results. The amplification efficiency of all qPCR primers was validated via standard curves constructed from serially diluted cDNA templates (typically 2-fold or 10-fold dilutions). Amplification efficiency (E) was calculated using the formula E = (10^(-1/slope) - 1)*100%. The efficiency for all primers used fell within the range of 90%–110%, with R² values for the standard curves greater than 0.98, meeting the recommended criteria of the MIQE guidelines. All reactions produced a single sharp peak in the melt curve analysis, confirming amplification specificity without nonspecific amplification or primer-dimer formation. Three technical replicates were performed for each biological replicate. The Ct values of the three technical replicates for each biological replicate were first averaged to obtain a representative Ct value for that biological replicate. Subsequently, all group-based statistical analyses and data presentations were performed using these consolidated Ct values, each representing one biological replicate. The relative quantification of mRNAs, lncRNAs, and miRNAs was calculated by the 2-ΔΔCt method using chs and U6 as the internal reference (Livak and Schmittgen 2001). The stability of the reference genes chs and U6 was evaluated using the geNorm and NormFinder software. Their expression remained stable across all experimental conditions, with an M value less than 0.5, confirming their suitability as references for data normalization. Statistical analyses Statistical analyses were performed using SPSS Statistics 20.0 (SPSS Inc., Chicago, IL, USA). Unless otherwise specified, values are expressed as the mean ± standard error of the mean (SEM). P < 0.05 was considered statistically significant. Abbreviations lncRNAs Long non-coding RNAs miRNAs Micro RNAs ceRNA Competing endogenous RNA cDNA Complementary DNA scRNA Small cytoplasmic RNA rRNA Ribosomal RNA snoRNA Small nucleolar RNA snRNA Small nuclear RNA tRNA Transfer RNA mRNA Messenger RNA T. mentagrophytes Trichophyton mentagrophytes qRT-PCR Quantitative real-time polymerase chain reaction RNA-seq RNA sequencing RISC RNA-induced Silencing Complex UTR Untranslated region PAGE Polyacrylamide gel electrophoresis 8 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae FPKM Fragment per kilobase of transcript per million mapped reads PCA Principal component analysis FDR False discovery rate TPM Transcripts per million GO Gene ontology KEGG Kyoto Encyclopedia of Genes and Genomes GSEA Gene Set Enrichment Analysis PPI Protein-Protein interactio EPC Edge Percolated Component MNC Maximum Neighborhood Component MCODE Molecular Complex Detection MREs MiRNA response elements SCC Spearman Rank correlation coefficient PCC Pearson correlation coefficient SEM Standard error of the mea MAPK Mitogen-activated protein kinase Results Germination of T. mentagrophytes spores Germination of T. mentagrophytes spores progressed through two distinct phases: swelling and germ tube formation. Dormant spores displayed a rounded or oval morphology (Fig. 1A). Within 6 hours of incubation, spore swelling commenced, resulting in an approximate doubling of cellular diameter. Concurrently, polarized growth was initiated at one site on the spore surface (Fig. 1B). By 12 hours, the germ tube emergence phase was evident, characterized by the protrusion of a single germ tube (Fig. 1C). Extensive growth of multiple germ tubes, culminating in hyphal formation, was observed by 18 hours (Fig. 1D; Suppl. material 1: fig. S1). Overview of RNA-sequencing To characterize the expression profiles and co-expression networks of mRNAs, lncRNAs, and miRNAs during T. mentagrophytes germination, cDNA and small RNA libraries were constructed and subjected to high-throughput sequencing. For the lncRNA-mRNA transcriptome, 1,567,771,788 high-quality clean reads (Q30 > 93%) were retained after filtering raw data (1,570,717,414 reads; Suppl. material 2: table S1). Base composition and coverage analyses indicated uniform genomic distribution without 3′/5′ bias, with > 77% of reads exhibiting ≥ 80% gene coverage (Fig. 2A, B). Sequencing saturation analysis confirmed adequate depth for capturing expressed genes (Suppl. material 1: fig. S2). Small RNA sequencing yielded 136,978,282 clean reads (Suppl. material 2: table S1), with distinct size distributions: 22-nt RNAs dominated in spores, whereas 23-nt RNAs were predominant in hyphae (Fig. 2C, D). After removing known non-coding RNAs in GeneBank (rRNA, scRNA, snoRNA, snRNA, and tRNA), 80,548,874 unmapped tags were retained (Suppl. material 1: fig. S3A). Subsequent genome alignment identified 102,779,029 mapped tags, including 7,548,666 exon-matching tags (Suppl. material 1: fig. S3B, C), with no repeat 9 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae sequence matches detected (Suppl. material 1: fig. S3D). Collectively, these results demonstrate high-quality, reproducible sequencing data suitable for downstream bioinformatic analyses. Analysis of mRNAs Identification and characterization of mRNAs To identify unannotated transcripts, we performed de novo transcriptome assembly using StringTie. Alignment of reconstructed transcripts to the T. mentagrophytes genome revealed 8,059 mRNAs, comprising 7,554 known and 505 novel transcripts (Suppl. material 2: table S2). Expression levels were quantified using FPKM (Fig. 3A), and violin plots demonstrated distinct mRNA expression patterns between spores and hyphae (Fig. 3B). Principal component analysis (PCA) and correlation analysis further confirmed clear separation between spore and hyphal groups (Fig. 3C, D). Differential expression analysis (FDR < 0.05, |log2FC| > 1) identified 3,193 significantly differentially expressed mRNAs, including 692 up-regulated and 2,501 down-regulated transcripts in hyphae compared to spores (Suppl. material 2: table S2). Notably, the most highly up-regulated mRNAs included SRY1 (g3940), YIL010W (g3025), and alg2 (g3846), while the most strongly down-regulated A B C D Figure 1. T. mentagrophytes observed by optical microscopy during germination. A. 0 h, B. 6 h, C. 12 h, D. 18 h. Scale bar: 10 μm. 16 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae AMP-activated protein kinase activity, and glutaminase activity) (Fig. 9B; Suppl. material 2: table S7), and 105 biological process terms (particularly positive regulation of G2/M transition, establishment of cell polarity, and differentiation-related morphogenesis) (Fig. 9C; Suppl. material 2: table S7). These findings strongly suggest antisense lncRNAs play crucial roles in mitotic regulation and spore activation. KEGG pathway analysis further supported these observations, with enrichment in: Yeast MAPK signaling pathway, Eukaryotic ribosome biogenesis, Yeast cell cycle regulation, Oxidative phosphorylation, Amino acid biosynthesis, and Secondary metabolite biosynthesis (Fig. 9D; Suppl. material 2: table S7). The coordinated enrichment of these pathways highlights the potential involvement of antisense lncRNAs in fundamental cellular processes during fungal development and morphogenesis. Functional enrichment analysis of cis-lncRNAs Previous studies have established that lncRNAs can cis-regulate adjacent genes on the same allele (Yan et al. 2017). Applying a 10 kb genomic window (upstream or downstream) to identify potential cis-regulatory lncRNAs, we identified 1,158 significant cis-interactions involving 389 differentially expressed lncRNAs and 950 target mRNAs (Suppl. material 2: table S8). Figure 7. Identification and characterization of lncRNAs. A. Identification of novel lncRNAs. B. lncRNA type. C. FPKM distribution. D. lncRNA expression violin plot. p = 6.17E-147***. AB CD 17 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Functional enrichment analysis of these cis-regulated target mRNAs revealed significant enrichment in 160 functional categories (P < 0.05), comprising: 28 cellular component terms (e.g., fungal-type vacuole lumen, cell wall components), 50 molecular function terms (including fructose-bisphosphate aldolase activity, G protein-coupled peptide receptor activity, and ATP citrate synthase activity), and 82 biological process terms (notably fungal-type cell wall disassembly during cellular fusion, fructose 1,6-bisphosphate metabolism, and cell cycle regulation) (Fig. 10A–C; Suppl. material 2: table S8). These enriched terms strongly implicate cis-acting lncRNAs in critical developmental processes, particularly hyphal formation and spore activation. KEGG pathway analysis further demonstrated enrichment in key metabolic pathways (P < 0.05), including: Amino acid metabolism (tryptophan, valine/leucine/isoleucine biosynthesis), Carbohydrate metabolism (fructose and mannose), Energy metabolism (oxidative phosphorylation) (Fig. 10D; Suppl. material 2: table S8). Collectively, these findings demonstrate that cis-acting lncRNAs participate in fungal development by locally regulating genes involved in cell wall remodeling, metabolic reprogramming, and cellular differentiation during hyphae formation and spore activation. Figure 8. Analysis of differentially expressed lncRNAs. A. Volcano plot of lncRNAs. B. Principal component analysis. C. Heatmap of differentially expressed lncRNAs. A B C 18 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Functional enrichment analysis of trans-lncRNAs In addition to cis-regulation, lncRNAs can modulate gene expression through trans-acting mechanisms (Yan et al. 2017). Our analysis identified 247,586 significant co-expression relationships between 409 differentially expressed lncRNAs and 3,138 target mRNAs (Suppl. material 2: table S9). Functional enrichment of these trans-regulated targets revealed significant associations (P < 0.05) with key biological processes, including: 30 cellular component terms (e.g., fungal-type cell wall, vacuolar lumen, hyphal cell wall), 53 molecular function terms (such as L-amino acid transmembrane transporter activity and DNA-binding transcription factor activity), and 192 biological process terms (including alpha-amino acid metabolic process, pigment biosynthetic Figure 9. GO and KEGG classification of antisense lncRNAs – target mRNAs. A. Top 20 GO terms enriched by cellular components. B. Top 20 GO terms enriched by molecular function. C. Top 20 GO terms enriched by biological process. D. Top 20 pathways of KEGG enrichment analysis. A B C D 19 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae process, and adhesion of symbiont to host) (Fig. 11A–C; Suppl. material 2: table S9). KEGG pathway analysis further identified 17 significantly enriched metabolic pathways (P < 0.05), notably encompassing amino acid biosynthesis (tryptophan, arginine/proline, and branched-chain amino acids), carbohydrate metabolism (fructose and mannose), lipid metabolism (glycerolipids metabolism), and cofactor synthesis (pantothenate and CoA biosynthesis) (Fig. 11D; Suppl. material 2: table S9). These comprehensive findings demonstrate that trans-acting lncRNAs likely orchestrate fungal development by globally regulating genes involved in cell wall organization, metabolic reprogramming, and host-microbe interactions. Figure 10. GO and KEGG classification of cis-lncRNAs target mRNAs. A. The top 20 enriched GO terms of the cellular component. B. The top 20 enriched GO terms of the molecular function. C. The top 20 enriched GO terms of the biological process. D. Top 20 of KEGG enrichment analysis. A B CD 20 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Analysis of miRNAs Identification and characterization of miRNAs Our small RNA sequencing analysis identified 733 known miRNAs (miRBase-matching sequences) through alignment with the miRBase database (Suppl. material 2: table S10) and predicted 52 novel miRNAs based on genomic positioning and hairpin structure analysis (Suppl. material 2: table S10). Both known and novel miRNAs exhibited a characteristic 5’ uracil bias in the 18–25 nt size range across spore and hyphal stages (Suppl. material 1: fig. S4A–D), with position-specific nucleotide preferences consistent with canonical miRNA features (Suppl. material 1: fig. S4E–H). Comprehensive annotation of 129,717,858 small RNA tags revealed diverse RNA species, including 44.5 Figure 11. GO and KEGG classification of trans-lncRNAs target mRNAs. A. The top 20 enriched GO terms of the cellular component. B. The top 20 enriched GO terms of the molecular function. C. The top 20 enriched GO terms of the biological process. D. Top 20 of KEGG enrichment analysis. A B C D 21 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae million rRNAs, 7.5 million exon-mapping sequences, 574,139 known miRNAs, and 38,066 novel miRNAs (Suppl. material 1: fig. S5A). Notably, TPM-based expression analysis revealed significant differences in miRNA abundance between spores and hyphae (Suppl. material 1: fig. S5B), suggesting stage-specific regulatory roles during fungal development. Identification and analysis of differentially expressed miRNAs PCA revealed distinct clustering patterns between spore and hyphal groups for both known and novel miRNAs (Fig. 12A, B). Differential expression analysis identified 119 significantly differentially expressed miRNAs (P < 0.05, |log2FC| > 1), comprising 56 upregulated and 63 downregulated species (Suppl. material 2: table S10). Notably, novel-m0011-5p, miR2109-z, and novelm0019-5p emerged as the most strongly upregulated miRNAs, while miR319-y, miR-12295-x, and miR6149-x showed the most pronounced downregulation (Fig. 12C). Hierarchical clustering of these differentially expressed miRNAs clearly distinguished hyphal from spore samples (Fig. 12D), demonstrating robust stage-specific miRNA expression profiles during fungal development. Functional enrichment analysis of miRNAs Through comprehensive target prediction, we identified 8,662 mRNAs potentially regulated by 785 miRNAs, encompassing 626,128 target sites (Suppl. material 2: table S11). Functional enrichment analysis of these miRNA-targeted mRNAs revealed significant associations (P < 0.05) with 19 functional categories, including plasma membrane (cellular component), transferase/oxidoreductase activity (molecular function), and key biological processes such as multi-organism reproduction, growth, and mitotic cell cycle regulation (Fig. 13A–C; Suppl. material 2: table S11). KEGG pathway analysis further demonstrated enrichment in 140 metabolic and signaling pathways, most notably biosynthesis-related processes, including secondary metabolites, amino acids, and cofactors, as well as ribosome biogenesis and yeast MAPK signaling (Fig. 13D; Suppl. material 2: table S11). These findings strongly suggest that miRNAs play a pivotal role in coordinating fungal growth, development, and metabolic adaptation through widespread post-transcriptional regulation. Analysis of ceRNAs Construction of a candidate ceRNA network Through comprehensive target prediction, we identified 34,680 miRNA-mRNA and 3,227 miRNA-lncRNA interaction pairs involving 119 differentially expressed miRNAs, 3,177 mRNAs, and 403 lncRNAs. Using stringent correlation thresholds (SCC ≤ -0.7 for negative co-expression and PCC > 0.9 for ceRNA pairs), we derived 229,789 potential ceRNA interactions between 2,911 mRNAs and 338 lncRNAs. For statistical screening of high-confidence pairs, we performed hypergeometric testing and retained interactions with an uncorrected P-value < 0.05 (note: multiple-testing correction such as FDR adjustment was not applied in this step), ultimately yielding a candidate network comprising 22 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae 14,360 significant ceRNA pairs, integrating 2,627 mRNAs, 107 miRNAs, and 329 lncRNAs (Suppl. material 2: table S12). Topological analysis revealed 636 hub nodes in the primary network tier, with the highest connectivity observed for five mRNAs (glt1, dtxS1, g3795, SPBC20F10.07, and MSTRG.440) and five lncRNAs (MSTRG.9453.1, MSTRG.2311.1, MSTRG.2710.1, MSTRG.3534.1 and MSTRG.8002.1), along with their miRNA partners (Fig. 14), highlighting central regulators in the fungal ceRNA network. Exploratory enrichment analysis of ceRNAs Functional annotation of ceRNA-related mRNAs revealed significant enrichment (uncorrected P-values < 0.05) in 286 categories (32 cellular components, 68 molecular functions, and 186 biological processes), including fungal-type vacuole lumen, fungal-type cell wall, hyphal cell wall, L-amino acid transmembrane Figure 12. Identification and characterization of miRNAs. A. PCA of known miRNAs. B. PCA of novel miRNAs. C. Volcano plot of miRNAs. D. Heatmap of differentially expressed miRNAs. A B CD 23 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae transporter activity, DNA-binding transcription factor activity, L-amino acid transport, methionine metabolic process, and cellular amino acid biosynthetic process (Fig. 15A–C; Suppl. material 2: table S12). KEGG pathway analysis further identified 18 significantly enriched metabolic pathways (uncorrected P-values < 0.05), with predominant representation in amino acid biosynthesis (tryptophan), secondary metabolite production, and central carbon metabolism (glycerolipid and pyruvate metabolism) (Fig. 15D; Suppl. material 2: table S12). These findings provide preliminary clues that lncRNAs modulate fungal development and metabolism through miRNA-mediated ceRNA networks, competitively regulating mRNAs involved in cell wall dynamics and metabolic reprogramming. Figure 13. GO and KEGG classification of miRNAs target mRNAs. A. Top 20 GO terms enriched by cellular components. B. Top 20 GO terms enriched by molecular function. C. Top 20 GO terms enriched by biological process. D. Top 20 pathways of KEGG enrichment analysis. A B C D 24 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae qRT-PCR verification of the RNA-Seq results To validate the RNA sequencing data, qRT-PCR was performed on a randomly selected panel of differentially expressed mRNAs, lncRNAs, and miRNAs using primers designed via Primer-BLAST (Suppl. material 2: table S13). Expression trends of mRNAs and lncRNAs exhibited significant concordance with RNA-seq profiles (Fig. 16; Suppl. material 2: table S13). Among miRNAs, miR-150-x showed significant upregulation during germination, whereas three others were down-regulated (Fig. 16). Critically, the positive correlation between up-regulated lncRNA-MSTRG.10182.6 and up-regulated target gene ro-4 aligned with the predicted ceRNA network interaction. These results collectively confirm the reliability of our transcriptomic data and the accuracy of identified expression dynamics. Figure 14. The highest connectivity for 5 mRNAs and 5 lncRNAs. Red represented mRNAs, yellow represented lncRNAs, and blue represented miRNAs. 25 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Discussion The transition from dormant spores to invasive hyphae in dermatophytes (e.g., Trichophyton rubrum, T. mentagrophytes) is orchestrated by multilayered molecular controls, including transcriptional, post-transcriptional, and epigenetic regulation. This process involves dynamic interactions between mRNAs, miRNAs, and lncRNAs, which collectively fine-tune fungal development and pathogenicity (Liu et al. 2007; Wang et al. 2018; Zhang et al. 2023). In the present study, we present a comprehensive transcriptomic landscape of the spore-toFigure 15. GO and KEGG classification of ceRNA-related mRNAs. A. Top 20 GO terms enriched by cellular components. B. Top 20 GO terms enriched by molecular function. C. Top 20 GO terms enriched by biological process. D. Top 20 pathways of KEGG enrichment analysis. A B C D 32 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae disrupting lncRNA-protein interactions could selectively inhibit spore germination without affecting host cells. In summary, this study systematically deciphered the lncRNA-mRNA-miRNA regulatory network during T. mentagrophytes germination by integrating multi-omics data, revealing how lncRNAs coordinate developmental transitions through cis-, trans-, and ceRNA mechanisms. These findings provide novel insights into the regulatory framework of filamentous fungal morphogenesis and lay a theoretical foundation for RNA interference-based antifungal strategies. Conclusion This study establishes a comprehensive regulatory atlas of T. mentagrophytes germination, revealing that: (1) Transcriptional reprogramming suppresses anabolism while activating cell division machinery. (2) lncRNAs operate through spatially distinct mechanisms (antisense, cis, and trans) to control morphogenesis. (3) miRNAs fine-tune developmental transitions by targeting cell cycle and metabolic regulators. (4) ceRNA networks integrate lncRNA-miRNA-mRNA interactions to coordinate hyphal growth. These findings provide novel insights into the regulatory framework of filamentous fungal morphogenesis and lay a theoretical foundation for RNA interference-based antifungal strategies. Acknowledgements We appreciate Gene Denovo Biotechnology Co. (Guangzhou, China) for assistance in sequencing and bioinformatics analysis. Additional information Conflict of interest The authors have declared that no competing interests exist. Ethical statement No ethical statement was reported. Use of AI No use of AI was reported. Adherence to national and international regulations All necessary permits were obtained. Funding This study was supported by National Natural Science Foundation of China (Grant Nos. U23A20398, 82030007, and 32200165), Noncommunicable Chronic Diseases-National Science and Technology Major Project (Grant Nos. 2024ZD0537707), Natural Science Foundation of Sichuan, China (Grant Nos., 2023NSFSC1553), Luzhou People’s Government-Southwest Medical University Science and Technology strategic cooperation project (Grant Nos. 2024LZXNYDJ034), Science and Technology Strategic Cooperation Programs of Sichuan University and Luzhou Municipal People’s Government (Grant Nos. 2021CDLZ7), and School-level project of Southwest Medical University (Grant Nos. 2018-ZRQN-121). 33 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Author contributions Conceptualization, Chunxiang Zhang, Wudian Xiao, and Jingcan You, Data curation, Zhaodan Wu, Jia Zhang, Jun Wan, and Xinyi Xiang; Formal analysis, Lvqin He and Wudian Xiao; Funding acquisition, Chunxiang Zhang and Wudian Xiao; Investigation, Zhaodan Wu, Jia Zhang, Yang Chen, Ziyu Wang, and Wudian Xiao; Methodology, Lvqin He, Lu Fu, Yang Yu, and Wudian Xiao; Software, Zhaodan Wu, Jingcan You, Kui Yang, and Ziyao Xiao; Visualization, Zhaodan Wu, Ruihuan Zhang, and Wudian Xiao; Writing – original draft, Zhaodan Wu, Jia Zhang, Wudian Xiao; Writing – review & editing, Chunxiang Zhang and Wudian Xiao. Author ORCIDs Wudian Xiao https://orcid.org/0000-0002-2718-4298 Data availability Data from this study have been deposited in public repositories as follows: Genomic raw reads and scaffolding data have been deposited to the Genome Sequence Archive (GSA) of the China National Center for Bioinformation (CNCB) under accession CRA028745. The final assembled and annotated genome is available from the CNCB Genome Warehouse (GWH) under accession GWHGQOF00000000.1. All transcriptomic sequencing data have been submitted to the NCBI Sequence Read Archive (SRA) under accessions SRR26663347–SRR26663352 (mRNA/lncRNA) and SRR26416206–SRR26416211 (miRNA). References Bitencourt TA, Neves-da-Rocha J, Martins MP et al. (2021) StuA-Regulated Processes in the Dermatophyte Trichophyton rubrum: Transcription Profile, Cell-Cell Adhesion, and Immunomodulation. Frontiers in Cellular and Infection Microbiology 11: 643659. https://doi.org/10.3389/fcimb.2021.643659 Bleichrodt RJ, Foster P, Howell G et al. 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(C) Sequencing saturation distribution of sample S3. (D) Sequencing saturation distribution of sample H1. (E) Sequencing saturation distribution of sample H2. (F) Sequencing saturation distribution of sample H3. figure S3. Classification of clean reads based on hierarchical genomic mapping. The mapping status of clean reads hierarchically aligned to non-coding RNA in GenBank (A), genome (B), exon regions (C), and repeat sequence (D). figure S4. Nucleotide bias analysis of known and novel miRNAs in hyphae and spore samples. First nuleotide bias of known miRNAs of hyphe (A) and spore (B). First nuleotide bias of novel miRNAs of hyphe (C) and spore (D). Nucleotide bias at each position of known miRNAs of hyphe (E) and spore (F). Nucleotide bias at each position of novel miRNAs of hyphe (G) and spore (H). figure S5. Analysis of small RNA composition and miRNA expression profile. (A) Comprehensive annotation of small RNA tags. (B) miRNA expression violin plot. p = 0.0416*. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/imafungus.16.166433.suppl1 40 IMA Fungus 16: e166433 (2025), DOI: 10.3897/imafungus.16.166433 Wudian Xiao et al.: mRNA, lncRNA, and miRNA in Trichophyton mentagrophytes spores and hyphae Supplementary material 2 Supplementary tables S1–S13 Authors: Wudian Xiao, Zhaodan Wu, Jia Zhang, Jun Wan, Ruihuan Zhang, Xinyi Xiang, Yang Yu, Lu Fu, Kui Yang, Yang Chen, Ziyao Xiao, Ziyu Wang, Lvqin He, Jingcan You, Chunxiang Zhang Data type: zip Explanation note: table S1. Summary of sequencing libraries for T. mentagrophytes spore and hyphal samples. table S2. Identification and differential expression analysis of mRNAs in T. mentagrophytes spore and hyphal samples. table S3. Functional enrichment analysis of differentially expressed mRNAs. table S4. Gene set enrichment analysis of differentially expressed mRNAs. table S5. Analysis of the protein-protein interaction network. table S6. Identification and differential expression analysis of lncRNAs. table S7. List of antisense lncRNA-mRNA regulatory pairs and their functional enrichment. table S8. List of cis lncRNA-mRNA regulatory pairs and their functional enrichment. table S9. List of trans lncRNA-mRNA regulatory pairs and their functional enrichment. table S10. Identification and differential expression analysis of miRNAs. table S11. Functional enrichment analysis of miRNA target genes. table S12. CeRNA network pairs and functional enrichment analysis of ceRNA-related mRNAs. table S13. Primer sequences and qRT-PCR validation results. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/imafungus.16.166433.suppl2