MicroRNAs constitute an additional layer in plant response to simultaneous bio- and abiotic stresses as exemplified by UV-B radiation and flg22-treatment on Arabidopsis thaliana.
Zheng ZhouDirk SchenkeEnhui ShenLongjiang FanDaguang CaiPublished in: Plant, cell & environment (2023)
Plants are confronted with various environmental stresses and develop sophisticated adaptive mechanisms. Our previous work demonstrated that the crosstalk of flg22 and ultraviolet (UV)-B-induced signalling cascades reprograms the expression of flavonol pathway genes (FPGs), benefiting plant defence responses. Although several transcription factors have been identified to be involved in this crosstalk, the underlying mechanism is largely unclear. Here, we analyzed microRNAs (miRNAs) and identified 126, 129 and 113 miRNAs with altered abundances compared to untreated control in flg22-, UV-B- and flg22/UV-B-treated seedlings, respectively. Two distinct modules were identified: The first consists of 10 miRNAs repressed by UV-B but up-regulated by flg22, and the second with five miRNAs repressed by flg22 but up-regulated by UV-B. In Arabidopsis, the knockdown of miR858a, a representative of module I, increased the abundance of CHS (a marker gene for FPGs), whereas its overexpression reduced CHS. Conversely, knockout of miR164b from module II decreased CHS and its overexpression increased CHS transcript levels. These data suggest a decisive role of miRNAs in the crosstalk. In the next, we described the interaction between miR858a and its target MYB111 (a positive regulator of FPGs) from module I in detail. We showed that MYB111 was profoundly post-transcriptionally regulated by miR858a during the crosstalk, whose expression was specifically but antagonistically controlled by UVR8- and FLS2-mediated signallings. Moreover, transcriptional monitoring using the GUS reporter gene demonstrates that miRNA-mediated posttranscriptional regulation is the main driving force in reprogramming the expression of FPGs and regulates plant adaptation to multiple concurrent environmental stresses.
Keyphrases
- transcription factor
- genome wide identification
- cell proliferation
- poor prognosis
- long non coding rna
- arabidopsis thaliana
- long noncoding rna
- dna binding
- genome wide
- copy number
- gene expression
- squamous cell carcinoma
- aqueous solution
- high glucose
- oxidative stress
- crispr cas
- cell wall
- endothelial cells
- big data
- risk assessment
- human health
- radiation therapy
- single molecule
- wastewater treatment
- electronic health record
- deep learning
- data analysis
- artificial intelligence
- rna seq
- newly diagnosed
- anaerobic digestion