A first de novo transcriptome assembly of feijoa (Acca sellowiana [Berg] Burret) reveals key genes involved in flavonoid biosynthesis.
Héctor ObertiJuan J Gutierrez-GonzalezClara PritschPublished in: The plant genome (2024)
Acca sellowiana [Berg] Burret, a cultivated fruit tree originating from South America, is gaining the attention of the nutraceutical and pharmaceutical industries due to their high content of flavonoids and other phenolic compounds in fruits, leaves, and flowers. Flavonoids are a diverse group of secondary metabolites with antioxidant, anti-inflammatory, and antimicrobial properties. They also play a crucial role in plant immune response. Despite their importance, the lack of research on A. sellowiana genomics and transcriptomics hinders a deeper understanding of the molecular mechanisms behind flavonoid biosynthesis and its regulation. Here, we de novo assembled and benchmarked 11 A. sellowiana transcriptomes from leaves and floral tissues at three developmental stages using high-throughput sequencing. We selected and annotated the best assembly according to commonly used metrics and databases. This reference transcriptome consisted of 221,649 nonredundant transcripts, of which 107,612 were functionally annotated. We then used this reference transcriptome to explore the expression profiling of key secondary metabolite genes. Transcripts from genes involved in the flavonoid and anthocyanin biosynthesis pathways were identified. We also identified 4068 putative transcription factors, with the most abundant families being bHLH, C2H2, NAC, MYB, and MYB-related. Transcript expression profiling revealed distinct patterns of gene expression during flower development. Particularly, we found 71 differentially expressed transcripts representing 14 enzymes of the flavonoid pathway, suggesting major changes in flavonoid accumulation across floral stages. Our findings will contribute to understanding the genetic basis of flavonoids and provide a foundation for further research and exploitation of the economic potential of this species.
Keyphrases
- transcription factor
- single cell
- genome wide
- gene expression
- rna seq
- genome wide identification
- dna methylation
- anti inflammatory
- immune response
- high throughput sequencing
- cell wall
- dna binding
- copy number
- staphylococcus aureus
- working memory
- inflammatory response
- essential oil
- oxidative stress
- machine learning
- human health