Abstract
The circadian clock synchronises plant physiology with environmental oscillations to promote plant fitness. The commonly-used methods for rhythm monitoring in dicots include rhythmic leaf movement tracking and luciferase-based imaging. For monocots, however, the leaf erectness makes these methods ineffective. Leveraging over 11,000 transcriptome samples, the circadian time-course profiling, the simulation-based algorithm optimisation, and the experimental validation, we developed SPIRAL, an online single time-point circadian analysis platform for rice and unexpectedly revealed a ∼28-hour endogenous rhythm in V4-stage Nipponbare leaves, making period-matched or long-day photoperiods comparatively more permissive growth conditions for the assayed experimental system. We demonstrated the versatility of SPIRAL by quantifying global rhythm sensitivity to abiotic stresses, pinpointing when nitrogen deficiency starts to perturb rhythms, a temporal resolution surpassing that of the state-of-the-art methods, and identifying candidate components connecting the clock to stresses through factorial analyses. Online deployment of SPIRAL enables platform-independent analysis of public and user-supplied rice transcriptomes to accelerate discoveries in crop adaptation and chronoculture.