Virulence- and signaling-associated genes display a preference for long 3'UTRs during rice infection and metabolic stress in the rice blast fungus.
Julio Rodríguez-RomeroMarco MarconiVíctor Ortega-CampayoMarie DemuezMark D WilkinsonAne SesmaPublished in: The New phytologist (2018)
Generation of mRNA isoforms by alternative polyadenylation (APA) and their involvement in regulation of fungal cellular processes, including virulence, remains elusive. Here, we investigated genome-wide polyadenylation site (PAS) selection in the rice blast fungus to understand how APA regulates pathogenicity. More than half of Magnaporthe oryzae transcripts undergo APA and show novel motifs in their PAS region. Transcripts with shorter 3'UTRs are more stable and abundant in polysomal fractions, suggesting they are being translated more efficiently. Importantly, rice colonization increases the use of distal PASs of pathogenicity genes, especially those participating in signalling pathways like 14-3-3B, whose long 3'UTR is required for infection. Cleavage factor I (CFI) Rbp35 regulates expression and distal PAS selection of virulence and signalling-associated genes, tRNAs and transposable elements, pointing its potential to drive genomic rearrangements and pathogen evolution. We propose a noncanonical PAS selection mechanism for Rbp35 that recognizes UGUAH, unlike humans, without CFI25. Our results showed that APA controls turnover and translation of transcripts involved in fungal growth and environmental adaptation. Furthermore, these data provide useful information for enhancing genome annotations and for cross-species comparisons of PASs and PAS usage within the fungal kingdom and the tree of life.
Keyphrases
- genome wide
- biofilm formation
- pseudomonas aeruginosa
- escherichia coli
- staphylococcus aureus
- dna methylation
- copy number
- antimicrobial resistance
- candida albicans
- minimally invasive
- poor prognosis
- bioinformatics analysis
- cystic fibrosis
- gene expression
- genome wide analysis
- big data
- electronic health record
- risk assessment
- high resolution
- climate change
- health information
- atomic force microscopy
- long non coding rna
- transcription factor
- deep learning