Biophysical JournalSystems BiologyPeer-reviewed journal article
Early detection of daylengths with a feedforward circuit coregulated by circadian and diurnal cycles
Abstract
Light-entrained circadian clocks confer rhythmic dynamics of cellular and molecular activities to animals and plants. These intrinsic clocks allow stable anticipations to light-dark (diel) cycles. Many genes in the model plant Arabidopsis thaliana are regulated by diel cycles via pathways independent of the clock, suggesting that the integration of circadian and light signals is important for the fitness of plants. Previous studies of light-clock signal integrations have focused on moderate phase adjustment of the two signals. However, dynamical features of integrations across a broad range of phases remain elusive. We recently found that phosphorylation of RIBOSOMAL PROTEIN OF THE SMALL SUBUNIT 6 (RPS6 or eS6), a ubiquitous post-translational modification across kingdoms, is influenced by the circadian clock and the light-dark (diel) cycle in an opposite manner. In order to understand this striking phenomenon and its underlying information processing capabilities, we built a mathematical model for the eS6-P control circuit. We found that the dynamics of eS6-P can be explained by a feedforward circuit with inputs from both circadian and diel cycles. Furthermore, the early-day response of this circuit with dual rhythmic inputs is sensitive to the changes in daylength, including both transient and gradual changes observed in realistic light intervals across a year, due to weather and seasons. By analyzing published gene expression data, we found that the dynamics produced by the eS6-P control circuit can be observed in the expression profiles of a large number of genes. Our work provides mechanistic insights into the complex dynamics of a ribosomal protein, and it proposes a previously underappreciated function of the circadian clock which not only prepares organisms for normal diel cycles but also helps to detect both transient and seasonal changes with a predictive power.
- organism: Arabidopsis
- assay: DNA methylation
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 8
- FWCI
- 0.64
- Field percentile
- top 38%
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