Accurate timekeeping is controlled by a cycling activator in Arabidopsis.

Transcriptional feedback loops are key to circadian clock function in many organisms. Current models of the Arabidopsis circadian network consist of several coupled feedback loops composed almost exclusively of transcriptional repressors. Indeed, a central regulatory mechanism is the repression of evening-phased clock genes via the binding of morning-phased Myb-like repressors to evening element (EE) promoter motifs. We now demonstrate that a related Myb-like protein, REVEILLE8 (RVE8), is a direct transcriptional activator of EE-containing clock and output genes. Loss of RVE8 and its close homologs causes a delay and reduction in levels of evening-phased clock gene transcripts and significant lengthening of clock pace. Our data suggest a substantially revised model of the circadian oscillator, with a clock-regulated activator essential both for clock progression and control of clock outputs. Further, our work suggests that the plant clock consists of a highly interconnected, complex regulatory network rather than of coupled morning and evening feedback loops. DOI:http://dx.doi.org/10.7554/eLife.00473.001

REVEILLE8 and PSEUDO-REPONSE REGULATOR5 Form a Negative Feedback Loop within the Arabidopsis Circadian Clock

Circadian rhythms provide organisms with an adaptive advantage, allowing them to regulate physiological and developmental events so that they occur at the most appropriate time of day. In plants, as in other eukaryotes, multiple transcriptional feedback loops are central to clock function. In one such feedback loop, the Myb-like transcription factors CCA1 and LHY directly repress expression of the pseudoresponse regulator TOC1 by binding to an evening element (EE) in the TOC1 promoter. Another key regulatory circuit involves CCA1 and LHY and the TOC1 homologs PRR5, PRR7, and PRR9. Purification of EE–binding proteins from plant extracts followed by mass spectrometry led to the identification of RVE8, a homolog of CCA1 and LHY. Similar to these well-known clock genes, expression of RVE8 is circadian-regulated with a dawn phase of expression, and RVE8 binds specifically to the EE. However, whereas cca1 and lhy mutants have short period phenotypes and overexpression of either gene causes arrhythmia, rve8 mutants have long-period and RVE8-OX plants have short-period phenotypes. Light input to the clock is normal in rve8, but temperature compensation (a hallmark of circadian rhythms) is perturbed. RVE8 binds to the promoters of both TOC1 and PRR5 in the subjective afternoon, but surprisingly only PRR5 expression is perturbed by overexpression of RVE8. Together, our data indicate that RVE8 promotes expression of a subset of EE–containing clock genes towards the end of the subjective day and forms a negative feedback loop with PRR5. Thus RVE8 and its homologs CCA1 and LHY function close to the circadian oscillator but act via distinct molecular mechanisms

Wheels within wheels: the plant circadian system

Circadian clocks integrate environmental signals with internal cues to coordinate diverse physiological outputs so that they occur at the most appropriate season or time of day. Recent studies using systems approaches, primarily in Arabidopsis, have expanded our understanding of the molecular regulation of the central circadian oscillator and its connections to input and output pathways. Similar approaches have also begun to reveal the importance of the clock for key agricultural traits in crop species. In this review, we discuss recent developments in the field, including a new understanding of the molecular architecture underlying the plant clock; mechanistic links between clock components and input and output pathways; and our growing understanding of the importance of clock genes for agronomically important traits

Circadian phase has profound effects on differential expression analysis.

Circadian rhythms are physiological and behavioral cycles with a period of approximately 24 hours that are generated by an endogenous clock, or oscillator. Found in diverse organisms, they are precisely controlled and provide growth and fitness benefits. Numerous microarray studies examining circadian control of gene expression have reported that a substantial fraction of the genomes of many organisms is clock-controlled. Here we show that a long-period mutant in Arabidopsis, rve8-1, has a global alteration in phase of all clock-controlled genes. After several days in constant environmental conditions, at which point the mutant and control plants have very different circadian phases, we found 1557 genes to be differentially expressed in rve8-1, almost all of which are clock-regulated. However, after adjusting for this phase difference, only a handful show overall expression level differences between rve8-1 and wild type. Thus the apparent differential expression is mainly due to the phase difference between these two genotypes. These findings prompted us to examine the effect of phase on gene expression within a single genotype. Using samples of wild-type plants harvested at thirty-minute intervals, we demonstrated that even this small difference in circadian phase significantly influences the results of differential expression analysis. Our study demonstrates the robust influence of the circadian clock on the transcriptome and provides a cautionary note for all biologists performing genome-level expression analysis

Additional file 5 of A custom library construction method for super-resolution ribosome profiling in Arabidopsis

Additional file 5: Figure S1. Precise ribonuclease digestion yields a clear band between 28 and 30 nt. Figure S2. qPCR quantification of circularized cDNAs and estimation of template volumes needed for library construction PCR. Figure S3. Comparison of rRNA contamination in our previous and current datasets. Figure S4. High correlations among three technical replicates of Ribo-seq data. Figure S5. Comparable strong 3-nt periodicity in our current data. Figure S6. Abundant contamination sequences present at 25 nt. Figure S7. Mapping and contamination statistics. Contaminant sequences considered include rRNAs/tRNAs/snRNAs/snoRNAs and overrepresented non-coding RNAs. Their sequences are listed in Additional file 3