Data files and analysis scripts for Seaton et al. "Photoperiodic control of the Arabidopsis proteome reveals a translational coincidence mechanism", bioRxiv 2017, Mol. Syst. Biol. 2018

Abstract

Dataset description: The dataset comprises transcriptome (RNA levels) and proteome (protein levels) data for samples of the plant Arabidopsis thaliana, the alga Ostreococcus tauri and the cyanobacterium Cyanothece, along with analysis scripts in the python language, and analysis outputs, for the publication described below:

Article abstract: Plants respond to seasonal cues, such as the photoperiod, to adapt to current conditions and to prepare for environmental changes in the season to come. To assess photoperiodic responses at the protein level, we quantified the proteome of the model plant Arabidopsis thaliana by mass spectrometry across four photoperiods. This revealed coordinated changes of abundance in proteins of photosynthesis, primary and secondary metabolism, including pigment biosynthesis, consistent with higher metabolic activity in long photoperiods. Higher translation rates in the daytime than the night likely contribute to these changes via rhythmic changes in RNA abundance. Photoperiodic control of protein levels might be greatest only if high translation rates coincide with high transcript levels in some photoperiods. We term this proposed mechanism 'translational coincidence', mathematically model its components, and demonstrate its effect on the Arabidopsis proteome. Datasets from a green alga and a cyanobacterium suggest that translational coincidence contributes to seasonal control of the proteome in many phototrophic organisms. This may explain why many transcripts but not their cognate proteins exhibit diurnal rhythms.