Structure of the Mating-Type Genes and Mating Systems of Verpa bohemica and Verpa conica (Ascomycota, Pezizomycotina).
Wenhua SunWei LiuYingli CaiXiaofei ShiLiyuan WuJin ZhangLingfang ErQiuchen HuangQi YinZhiqiang ZhaoPeixin HeFu-Qiang YuPublished in: Journal of fungi (Basel, Switzerland) (2023)
Verpa spp. are potentially important economic fungi within Morchellaceae. However, fundamental research on their mating systems, the key aspects of their life cycle, remains scarce. Fungal sexual reproduction is chiefly governed by mating-type genes, where the configuration of these genes plays a pivotal role in facilitating the reproductive process. For this study, de novo assembly methodologies based on genomic data from Verpa spp. were employed to extract precise information on the mating-type genes, which were then precisely identified in silico and by amplifying their single-ascospore populations using MAT-specific primers. The results suggest that the MAT loci of the three tested strains of V. bohemica encompassed both the MAT1-1-1 and MAT1-2-1 genes, implying homothallism. On the other hand, amongst the three V. conica isolates, only the MAT1-1-1 or MAT1-2-1 genes were present in their MAT loci, suggesting that V. conica is heterothallic. Moreover, bioinformatic analysis reveals that the three tested V. bohemica strains and one V. conica No. 21110 strain include a MAT1-1-10 gene in their MAT loci, while the other two V. conica strains contained MAT1-1-11 , exhibiting high amino acid identities with those from corresponding Morchella species. In addition, MEME analysis shows that a total of 17 conserved protein motifs are present among the MAT1-1-10 encoded protein, while the MAT1-1-11 protein contained 10. Finally, the mating type genes were successfully amplified in corresponding single-ascospore populations of V. bohemica and V. conica , further confirming their life-cycle type. This is the first report on the mating-type genes and mating systems of Verpa spp., and the presented results are expected to benefit further exploitation of these potentially important economic fungi.
Keyphrases
- genome wide
- genome wide identification
- life cycle
- bioinformatics analysis
- amino acid
- dna methylation
- escherichia coli
- genome wide analysis
- copy number
- transcription factor
- healthcare
- oxidative stress
- small molecule
- mental health
- protein protein
- gene expression
- electronic health record
- genome wide association study
- artificial intelligence
- deep learning
- genome wide association
- cell wall