Journal of The Royal Society InterfacePlant BiologyPeer-reviewed journal article
Data-driven mathematical modelling explains altered timing of EARLY FLOWERING 3 in the wheat circadian oscillator
Abhishek UpadhyayiD, Jamila Rowland-ChandleriD, Julia Stewart-WoodiD, Gabriela Pingarron-CardenasiD, Isao T. TokudaiD, Alex A. R. WebbiD, James C W LockeiD
Abstract
Circadian rhythms, daily oscillations with a free-running period of approximately 24 hours, have evolved in organisms across the kingdoms of life, enabling organisms to anticipate and adapt to environmental cycles. Circadian timing in plants is governed by an oscillator gene network of transcriptional regulators that exists in each cell. Wheat provides an opportunity to investigate the mechanisms of the plant circadian oscillator in an important agricultural species. We recently found that a single oscillator component EARLY FLOWERING 3 is expressed at a different time in wheat compared to the model plant Arabidopsis. This was unexpected since there is remarkable conservation of timing of activity of the different oscillator components within a kingdom, for example, even when animals switch from nocturnal to diurnal activity. We have examined how the change in timing of ELF3 transcription between Arabidopsis and wheat has occurred and its implications for circadian oscillator function. We describe an optimised computational model of the wheat circadian oscillator that is informed by experimental data and the structure of the promoter elements driving oscillator gene expression. Our optimised computational models suggest that the dawn-expression of the key oscillator gene ELF3 in wheat occurs due to repression of the ELF3 promoter by TOC1. Our simulations predict that plant circadian oscillators are robust against changes in ELF3 timing. Our work demonstrates that plant circadian oscillators can have a flexible architecture such that different oscillator structures can originate circadian rhythms.
- organism: plant (other)
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 2
- FWCI
- 3.68
- Field percentile
- top 14%
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