Genomic Features of and the Transcriptional Regulation of Secondary Metabolite Biosynthesis.

Fungal secondary metabolites (SMs) have broad applications in biomedicine, biocontrol, and the food industry. In this study, whole-genome sequencing and annotation of were conducted, followed by comparative genomic analysis with 11 other species of Polyporales to examine genomic variations and secondary metabolite biosynthesis pathways. Additionally, transcriptome data were used to analyze the differential expression of polyketide synthase (PKS), terpene synthase (TPS) genes, and transcription factors (TFs) under different culture conditions. The results show that differs from other fungal species in genome size (34.58 Mb) and GC content (50.72%). The antibiotics and Secondary Metabolites Analysis Shell (AntiSMASH) analysis reveals significant variation in the number of SM biosynthetic gene clusters (SMBGCs) across the 12 species (12-29), with containing 25 SMBGCs: 4 PKS, 6 non-ribosomal peptide synthetase (NRPS), and 15 TPS clusters. The gene is hypothesized to be involved in the biosynthesis of orsellinic acid or its derivatives, while might catalyze the synthesis of 6-methylsalicylic acid (6MSA) and its derivatives. The genes are suggested to synthesize tetracyclic sesquiterpene type B trichothecene compounds, while may be involved in the synthesis of δ-cadinol, β-copaene, and α-murolene analogs or derivatives. Comparative genomic analysis shows that the genome size of is similar to that of , with comparable SMs. Both species share four types of PKS domains and five distinct types of TPS. Additionally, exhibits a high degree of similarity to , despite belonging to a different genus within the same family. Transcriptome analysis reveals significant variation in the expression levels of PKS and TPS genes across different cultivation conditions. The and genes, along with nine , are significantly upregulated under three solid culture conditions. In contrast, under three different liquid culture conditions, the , , and genes, along with twelve , exhibit higher activity. Co-expression network analysis and binding site prediction in the promoter regions of and genes suggest that and regulate expression. , , , and likely modulate transcriptional activity. and expression is likely regulated by and , respectively. This study provides new insights into the regulatory mechanisms of SMs in and offers potential strategies for enhancing the biosynthesis of target compounds through artificial intervention.