bioRxivMicrobiologyPreprint
Bacillus velezensis 9912 enhances rice growth by triggering plant hormone modulation and complex miRNA-mRNA regulatory networks
Abstract
Bacillus velezensis, a prominent member of plant growth-promoting bacteria, effectively suppresses pathogens and promotes plant growth. Despite its well-recognized efficacy, the intricate molecular mechanisms of its growth-promoting attributes remain largely unexplored. In this study, a commercial biopesticide B. velezensis 9912 significantly enhanced leaf photosynthesis and improved rice root development in the field experiment. And then, a rigorous hydroponic experiment was performed to investigate its underlying mechanism in plant growth promotion. High-throughput sequencing and bioinformatics analysis revealed 2,938 rice genes and 30 miRNAs responsive to strain 9912. Notably, differentially expressed genes encompassed key transcription factors like ERF, WRKY, and AP2. Remarkably, auxin-and ethylene-related genes were up-regulation significantly at day 1 and pectinesterase-related genes were up-regulation considerably at day 3, which revealed an unusual growth mechanism for strain 9912 to promote rice root development. In addition, DNA replication, cell cycle, cell division, and cytoskeleton organization were significantly enriched in GO and KEGG pathways. Biosynthetic pathways of secondary metabolites, such as carotenoid, lipid, diterpenoid, and brassinosteroid were also significantly enriched. An integrated analysis of the transcriptome and miRNAome identified several miRNA-mRNA regulatory networks, including miR166-Os08g14940, miR396-Os07g9320, miR529-Os12g31540, and miR6249-Os05g07880, which are involved in the process of growth promotion. In conclusion, our investigation offers insightful thoughts into the dynamic responses of rice genes and miRNAs to B. velezensis 9912, unveiling plant hormone modulation and potential miRNA-mRNA regulatory networks that are imperative in the growth promotion mechanism.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: biophysical modeling
- Citations
- 0
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