Abstract
AbstractThe apocarotenoid zaxinone promotes growth and suppresses strigolactone biosynthesis in rice. To shed light on the mechanisms underlying its growth-promoting effect, we employed a combined omics approach integrating transcriptomics and metabolomics analysis of rice seedlings treated with zaxinone, and determined the resulting changes at the cellular and hormonal levels. Metabolites as well as transcripts analysis demonstrate that zaxinone application increased sugar content and triggered glycolysis, the tricarboxylic acid cycle and other sugar-related metabolic processes in rice roots. In addition, zaxinone treatment led to an increased root starch content and induced glycosylation of cytokinins. The transcriptomic, metabolic and hormonal changes were accompanied by striking alterations of roots at cellular level, which showed an increase in apex length, diameter, and the number of cells and cortex cell layers. Remarkably, zaxinone did not affect the metabolism of roots in a strigolactone deficient mutant, suggesting an essential role of strigolactone in the zaxinone growth-promoting activity. Taken together, our results unravel zaxinone as a global regulator of the transcriptome and metabolome, as well as of hormonal and cellular composition of rice roots. Moreover, they suggest that zaxinone promotes rice growth most likely by increasing sugar uptake and metabolism, and reinforce the potential of this compound in increasing rice performance.
Original language | English (US) |
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Journal | Communications Biology |
Volume | 4 |
Issue number | 1 |
DOIs | |
State | Published - Oct 25 2021 |
Bibliographical note
KAUST Repository Item: Exported on 2021-10-29Acknowledged KAUST grant number(s): CRG2017, CRG2020
Acknowledgements: We thank Dr. Kennedy Odokonyero for technical support in photosynthesis experiments and Dr. Hendrik N. J. Kuijer for reading and correcting the manuscript. We are grateful to the KAUST bioscience core lab for RNA-seq, the members of the Bioactives lab in KAUST, members of AG Fernie in MPIMP, and Prof. Anna Fusconi and Prof. Paola Bonfante in the University of Torino for their helpful discussions and assistance. This work was supported by baseline funding and Competitive Research Grants (CRG2017 and CRG2020) given to S.A.-B. from King Abdullah University of Science and Technology (KAUST), and by grants from the European Union’s Horizon 2020 research and innovation programme, project PlantaSYST (SGA-CSA No. 739582 under FPA No. 664620) to A.R.F. and S.A.