Genome-wide studies of circadian transcription or mRNA translation have been hindered by the presence of heterogeneous cell populations in complex tissues such as the nervous system. We describe here the use of a Drosophila cell-specific translational profiling approach to document the rhythmic “translatome” of neural clock cells for the first time in any organism. Unexpectedly, translation of most clock-regulated transcripts—as assayed by mRNA ribosome association—occurs at one of two predominant circadian phases, midday or mid-night, times of behavioral quiescence; mRNAs encoding similar cellular functions are translated at the same time of day. Our analysis also indicates that fundamental cellular processes—metabolism, energy production, redox state (e.g., the thioredoxin system), cell growth, signaling and others—are rhythmically modulated within clock cells via synchronized protein synthesis. Our approach is validated by the identification of mRNAs known to exhibit circadian changes in abundance and the discovery of hundreds of novel mRNAs that show translational rhythms. This includes Tdc2, encoding a neurotransmitter synthetic enzyme, which we demonstrate is required within clock neurons for normal circadian locomotor activity.

The circadian clock controls daily rhythms in physiology and behavior via mechanisms that regulate gene expression. While numerous studies have examined the clock regulation of gene transcription and documented rhythms in mRNA abundance, less is known about how circadian changes in protein synthesis contribute to the orchestration of physiological and behavioral programs. Here we have monitored mRNA ribosomal association (as a proxy for translation) to globally examine the circadian timing of protein synthesis specifically within clock cells of Drosophila. The results reveal, for the first time in any organism, the complete circadian program of protein synthesis (the “circadian translatome”) within these cells. A novel finding is that most mRNAs within clock cells are translated at one of two predominant circadian phases—midday or mid-night—times of low energy expenditure. Our work also finds that many clock cell processes, including metabolism, redox state, signaling, neurotransmission, and even protein synthesis itself, are coordinately regulated such that mRNAs required for similar cellular functions are translated in synchrony at the same time of day.

Funding: This research was supported by NIH R01 HL59873 (FRJ), NIH R01 NS065900 (FRJ), a center grant to Tufts School of Medicine (P30 NS047243; PI, FRJ), a Pilot Award from the CNR (FRJ), a Young Investigator Award (NARSAD 17339) from the Brain and Behavior Research Foundation (YH), and a NIH Director's New Innovator Award (DP2 OD006446) to LGR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2013 Huang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Drosophila is an excellent model for cell-type–specific profiling of clock cells because of its outstanding genetics and well-characterized circadian system. Studies have described the fly circadian molecular oscillator [8] and the circadian neuronal circuitry [9] , revealing molecular and functional differences among groups of pacemaker neurons that mediate morning and evening bouts of activity or responses of the clock to environmental cues [5] , [10] – [18] . To date, no study has documented genome-wide expression profiles for all clock cells of the fly head or the complete translatome of such cells. In this study, we describe use of the Translating Ribosome Affinity Purification (TRAP) method [19] to define the rhythmic translatome of circadian clock cells. Our results reveal a daily synchronization of protein synthesis and identify novel cycling mRNAs within clock cells that are required for diverse physiological processes.

Genetic studies carried out in several model systems have provided seminal knowledge about the biochemistry of the circadian molecular oscillator and the neural circuitry regulating circadian behavior. The best characterized circadian oscillators consist of transcriptional/translational feedback loops (TTFLs) [1] , although nontranscriptional oscillators (NTOs) exist in organisms ranging from unicellulars to Drosophila and humans [2] – [4] . In Drosophila and mammals, a well-characterized TTFL oscillator consisting of several canonical clock genes regulates circadian behavioral rhythms (reviewed in [1] ). Similarly, transcription of many (perhaps most) genes is orchestrated by the circadian clock, based on gene profiling studies carried out in Drosophila, mammals and plants. Only a few studies, however, have documented cell-type–specific transcriptional rhythms [5] – [7] , due to methodological limitations. Most of those studies utilized Fluorescence-Activated Cell Sorting (FACS), the manual isolation of identified cells, or cell-specific transcriptional profiling techniques, but such methods are either not applicable to all cell populations or lack the sensitivity to detect the entire transcriptome; nor do they distinguish between ribosome-bound (i.e., translating) and soluble mRNA without the use of polyribosome isolation.

Results

Implementation of TRAP for Studies of Circadian Biology Previous studies have shown that TRAP reflects the translational status of mRNAs in a manner similar to that of conventional polyribosomal analysis [19]. In addition, a recent study in Drosophila indicates that an EGFP-L10a fusion incorporates into polysomes and can be employed for cell-specific translational profiling [20]. To employ TRAP in our studies, we generated Drosophila strains carrying a UAS-EGFP-L10a transgene insertion (see Materials and Methods). Using a pan-neuronal driver (elav-Gal4), we found that the EGFP-L10a fusion has a cytoplasmic/nucleolar pattern of localization in neurons (Figure 1A–C), consistent with incorporation into ribosomes. Indeed, the ring shape pattern in nucleoli (seen in the nucleus of Figure 1A) likely results from expression in the Granular Component (GC, Figure 1D), a structure within which ribosomal proteins assemble into functional ribosomes. As expected, EGFP-L10a was localized in all neurons of the adult nervous system (Figure 1E). In contrast, the tim-uas-Gal4 driver results in expression within the cytoplasm of clock neurons and glia of the nervous system (Figure 1F) or only clock neurons when combined with repo-Gal80 (Figure 1G), which inhibits expression in all glial cells. A different GFP–Drosophila ribosomal protein fusion (L11) has an identical intracellular localization pattern [21]. In addition, it has recently been shown that our EGFP-L10a fusion localizes to branch points of neuronal dendrites, consistent with incorporation into ribosomes that mediate local protein synthesis [22]. Collectively, these pieces of evidence indicate that EGFP-L10a incorporates into functional ribosomes. PPT PowerPoint slide

PowerPoint slide PNG larger image

larger image TIFF original image Download: Figure 1. Expression of EGFP-L10a and assays of function in clock cells. (A–C) Expression of EGFP-L10a in a large neurosecretory cell. Nu, nucleolus; N, Nucleus; C, Cytoplasm. Staining for a nuclear protein called LARK (red signal) is used to identify the nucleus. (D) Schematic representation of the structure of the nucleolus. FC, Fibrillar Center; DFC, Dense Fibrillar Components; GC, Granular Components. GC is the location of ribosome assembly. (E) Expression pattern of EGFP-L10a in the brain and ventral ganglion using the elav-Gal4 pan-neuronal driver. (F) Expression of EGFP-L10a in all clock cells driven by tim-Gal4. (G) Restricted expression of EGFP-L10a to clock neuron but not glia using a combination of tim-Gal4 and repo-Gal80. (H) Expression of EGFP-L10a in clock cells does not disrupt normal circadian behavior. Left panels shows representative free-running actograms of control flies and flies expressing EGFP-L10a in either PDF neurons (using pdf-Gal4) or all clock cells (using tim-Gal4). Right panels show the corresponding correlograms. (I) TRAP is capable of detecting changes in mRNA translation, as assayed by changes in the translational status of Ferritin 1 Heavy Chain Homolog (Fer1HCH) mRNA in response to overexpression of the Iron Regulatory Protein (IRP). Control, w1118; act5C-Gal4/tub-Gal80ts; UAS-EGFP-L10a/+. IRP overexpression, w1118; act5C-Gal4/tub-Gal80ts; UAS-EGFP-L10a/UAS-IRP. (J) Circadian changes in the translation of period (per) and timeless (tim) mRNAs. Genotype of the flies assayed, elav-Gal4; UAS-EGFP-L10a/+. Error bar represents standard error of the mean (SEM). *p<0.01; **p<0.001 (Student's t test). https://doi.org/10.1371/journal.pbio.1001703.g001 We examined circadian locomotor activity of flies overexpressing the UAS-EGFP-L10a transgene in clock cells (Pigment Dispersing Factor, PDF, or Timeless, TIM) to determine whether there were adverse effects on behavior. As shown in Figure 1H, these files have normal behavioral rhythmicity, indicating that EGFP-L10a does not act in a dominant negative manner even at high levels [Average periods (P) and Rhythmicity Indices (RI) were 23.7±0.08/0.57±0.02, 24.0±0.03/0.55±0.01, and 24.3±0.14/0.50±0.03 for control, pdf-Gal4>UAS-EGFP-L10a, and tim-uas-Gal4>UAS-EGFP-L10a flies; n = 17–30]. Thus, the presence of GFP-tagged ribosomes in clock cells does not affect their function.

TRAP Can Detect Changes in Translational Status We optimized TRAP methods for use with Drosophila and demonstrated that significant amounts of RNA could be immunoprecipitated from head tissues of flies expressing UAS-EGFP-L10a under control of the pan-neural elav-Gal4 or clock cell tim-uas-Gal4 driver (see Materials and Methods). Prior to pursuing genome-wide studies, we wished to determine if our Drosophila TRAP methods could detect bona fide changes in translational status. To ask this question, we employed overexpression of Iron Regulatory Protein (IRP), which is known to repress translation of an unspliced form of ferritin (fer) mRNA by inhibiting binding of the small ribosomal subunit to the message. We generated act5C-Gal4/tub-Gal80ts, UAS-EGFP-L10a/UAS-IRP flies in order to be able to activate expression of the TRAP and IRP transgenes conditionally during larval development (by raising temperature to inactivate Gal80ts, an inhibitor of Gal4). Larvae of this genotype and controls (act5C-Gal4/tub-Gal80ts; UAS-EGFP-L10a) were exposed to 30°C to activate expression of UAS-EGFP-L10a in both genotypes and additionally UAS-IRP in the experimental class. Early pupae were collected for both genotypes and subjected to TRAP coupled with Q-RT-PCR to quantify ribosome-associated fer mRNA (relative to control Rp49 mRNA). Similar to previous studies in Drosophila that employed polysome gradient analysis [23], we observed IRP-induced translational repression of an unspliced but not a spliced form of fer (Figure 1I). Indeed, translation of spliced fer was enhanced slightly by IRP overexpression, similar to that observed from the analysis of a high molecular weight polysome fraction in the previous study [23]. This result shows feasibility for the use of TRAP in Drosophila to detect changes in translational status. To determine if our methods were able to detect rhythmic changes in the ribosomal association of cycling transcripts, we examined the period (per) and timeless (tim) clock mRNAs. TRAP methods were employed to immunopurify RNA from head tissues of elav-Gal4/UAS-EGFP-L10a flies two times of day (ZT11 and ZT23, the times of high and low per/tim RNA abundance, respectively). Extracted RNA was then subjected to Q-RT-PCR, using gene-specific primers, to detect the clock mRNAs. Figure 1J shows that the abundances of ribosome-bound tim and per clock mRNAs are significantly higher at ZT11 than at ZT23. This result is consistent with the known rhythmic profile of tim and per RNA abundances at the two time points (higher at ZT11) and the expected translational status of the mRNA at the two times of day. We emphasize that Figure 1J shows differences in ribosome association of the clock RNAs, not simply the previously documented RNA abundance for per and tim. In addition, we note that the temporal resolution of our measurements does not exclude translational regulation of per mRNA, which has been suggested in certain studies [24]–[26]. Nonetheless, these results demonstrate that TRAP methods are capable of detecting diurnal changes in the translational status of specific mRNAs.

Clock Cell-Specific Expression Profiling Efficiently Detects Circadianly Translated RNAs Using the newly developed methods, we performed TRAP on head tissue lysates of tim-uas-Gal4; UAS-EGFP-L10a flies that were collected at 4-h intervals during the first two days of constant darkness (DD) following entrainment to LD 12∶12. Such flies express the EGFP-L10a fusion in all clock cells of the head, including the ∼150 pacemaker neurons, photoreceptors, and glia. RNA was extracted from affinity-purified samples and used to generate libraries representing all ribosome-associated transcripts (see Materials and Methods). TRAP libraries corresponding to six different times of the circadian cycle (CT0, 4, 8, 12, 16, and 20) were independently constructed for DD1 and DD2 (see details in Materials and Methods). Libraries were sequenced, using a multiplexing strategy, to produce single end, 100 base sequencing reads; these were mapped to the Drosophila reference genome and analyzed as described in Materials and Methods. We employed two recently developed programs, JTK_CYCLE and ARSER [27],[28], to compare their usefulness for detecting circadian rhythms in the ribosome association of mRNAs. Using criteria and statistical cutoffs described in the Materials and Methods section, 1,195 and 263 translationally cycling mRNAs were detected by the ARSER and JTK_CYCLE programs, respectively. Interestingly, the majority of the cycling mRNAs (203 out of 263) detected by JTK_CYCLE were also detected by the ARSER program (Figure 2A), indicating consistency of the two analyses. Figure S1 shows robust cycling for eight mRNAs out of the 60 identified by JTK_CYCLE but not ARSER. Thus, JTK_CYCLE may identify cycling mRNAs not detected by ARSER. Table S4 lists the 1,255 mRNAs that were identified as exhibiting significant translational cycling by either program (mRNAs identified by both programs are indicated in bold). The False Discovery Rate (FDR) calculated by the ARSER program at the relevant p value was 0.148, indicating that approximately 186 mRNAs are false positives. This FDR is quite low relative to other recent genome-wide studies of cycling mRNAs [29]–[31]. We did not compute an FDR for the JTK_CYCLE program, because 203/263 mRNAs identified by JTK_CYCLE are included in the ARSER dataset, and therefore the latter dataset represents a good approximation of FDR for our analyses. Based on the ARSER analysis, we estimate that approximately 1,069 of these mRNAs show circadian changes in translation in clock cells of the adult head, representing about 10% of all analyzed genes in the genome. This large number of cycling mRNAs is consistent with recent studies utilizing manual dissection approaches to perform cell-specific transcriptional profiling of the Drosophila PDF clock neurons [5],[10]. Cell-specific profiling methods may identify a larger number of cycling Drosophila mRNAs, relative to previous studies, due to a more homogeneous starting cell population (i.e., clock cells). PPT PowerPoint slide

PowerPoint slide PNG larger image

larger image TIFF original image Download: Figure 2. Identification of mRNAs displaying a circadian translational rhythm in clock cells. (A) Number of rhythmically translated genes identified by two different programs: JTK_CYCLE and ARSER. (B) Translational profile of known cycling genes. The y-axis represents normalized read counts. (C) Quantification of sequence reads aligned to the period (per) gene and a nearby nonrhythmic gene (CG2658) across the time-series. https://doi.org/10.1371/journal.pbio.1001703.g002

Known Cycling mRNAs Exhibit Translational Rhythms We examined a number of mRNAs in our datasets that had previously been shown to exhibit abundance rhythms to assess the quality of our datasets. These include both clock and clock-regulated mRNAs (per, tim, vri, clk, to, fer2, slob, ugt35b, 5-HT1A, bw, Ir, and WupA). All showed translational rhythmicity (Figure 2B) with an expected phase, although the tim rhythm damped on DD2. Figure 2C, for example, shows robust rhythmicity in the sequence reads for per and lack of rhythmicity for a nearby gene. Our analysis also revealed translational cycling for many other genes that express rhythmic mRNAs. For example, our list of mRNAs includes 49 of 420 mRNAs showing circadian abundance rhythms identified in five previous microarray-based studies (see Introduction). This comparison does not include a recent study that identified 2,751 cycling mRNAs in hand-dissected PDF neurons [10]; our results include 172 of those mRNAs (see Table S4). Interestingly, Ugt35b mRNA, one of several encoding fly glucuronosyltransferase activity, was previously shown to exhibit transcriptional cycling in head tissues but not in PDF neurons [10]. Given that we employed a clock cell tim-Gal4 driver in our TRAP studies, we suggest that Ugt35b cycles in other clock cells of the head. We conducted TRAP combined with quantitative PCR for Ugt35b, tim, and 18 novel cycling mRNAs (not previously found to show abundance rhythms in head tissues) to verify results obtained by RNA-seq. As expected, Ugt35b and tim exhibited rhythmicity, presumably a consequence of their mRNA abundance rhythms. Of the novel mRNAs, 15/18 showed rhythmic changes in translation, with a profile very similar to that observed with RNA-seq analysis (Figure S2). We further analyzed cycling of a number of these mRNAs in the per0 mutant, which lacks a functional clock, during the first day of constant darkness (DD1). We found that rhythmic expression of these mRNAs was abolished in the per0 mutant, confirming their circadian clock regulation (Figure S3).

Translational Profiling Reveals Circadianly Synchronized Protein Synthesis Previous genome-wide studies showed that peaks of mRNA abundance occur at many different circadian phases (see Figure S4). In contrast, our profiling of the clock cell translatome revealed a striking feature of circadianly regulated protein synthesis. We found that peak translation for most of the 1,255 mRNAs identified in our study occurs predominantly during two circadian phases: midday or mid-night (Figure 3A–C; Figure S4). These are times of relative behavioral quiescence and just prior to initiation of locomotor activity bouts (Figure 3A, lower panel). Thus, protein synthesis may be confined to times of day that require reduced metabolic expenditure and/or are just prior to initiation of behavioral activities. A further analysis revealed surprisingly synchronized translation of mRNAs required for the same cellular process: translation is predominantly unimodal (with a peak during the day or night) or biomodal, depending on the process (Figure 3C). This bias in the timing of translation was true of many other cellular processes (Figure 3D). For example, of the 10 enzymes involved in glucose metabolism in our list of cycling RNAs, nine are translated during the day. In contrast, all 10 GPCRs in our list are translated during the night (Figure 3E). PPT PowerPoint slide

PowerPoint slide PNG larger image

larger image TIFF original image Download: Figure 3. TRAP identifies two major phases of rhythmic translation. (A, Upper) A heat map showing the relative level of translation during DD days 1–2 for each of the 1,255 genes. Genes are arranged vertically according to their phases. (A, Lower) Population plot of free-running activity (DD days 1–2) for the fly strain used to generate the translational profiles (vertical axis, activity level; horizontal axis, time of day). n = 17, error bars are SEM. (B) Phase distributions of ribosome association for all cycling RNAs. (C) Phase distributions of cycling RNAs relevant for several different cellular processes. Horizontal axes show phase; vertical axes indicate the number of RNAs. (D) Day or night distribution for major biological processes. (E) Translational profiles of mRNAs representing two functional groups: G protein–coupled receptors (upper panel) and glucose metabolic enzymes (lower panel). https://doi.org/10.1371/journal.pbio.1001703.g003 Of note, mRNAs encoding a number of translational initiation factors (eIF4E isoforms) exhibit cycling with a phase that corresponds to the daytime peak of circadian translation (Figure S5). Thus, circadian translation of these eIFs may contribute to a broad clock regulation of protein synthesis. In contrast, the major initiation factor, eIF4E-1, does not exhibit translational cycling, suggesting that it does not participate in circadian regulation (Figure S5). Consistent with previous results indicating that ribosome biogenesis is regulated in a circadian manner [32], 20 mRNAs encoding ribosomal proteins, translation initiation factors, or other translational regulatory components show translational rhythmicity (Table S4).

Translational Regulation Contributes to Circadian Gene Expression The synchronized rhythmic expression profiles identified by our cell-specific profiling approach may result from a clock regulation of translation or mRNA abundance. To ask whether changes in translational status contribute to the synchronization of gene expression in clock cells, we carried out additional studies, using TRAP/RNA-seq methods. We reasoned that total RNA isolated from whole heads contains mRNAs from both clock and nonclock cells. Thus, if a gene is robustly expressed in nonclock cells, the abundance profile obtained from whole head total RNA will not represent its expression profile in clock cells. However, for mRNAs predominantly expressed in clock cells (such as per, tim, and others), assays of total head RNA will reflect clock cell expression. Such an mRNA ought to show enrichment in a TRAP sample from tim-uas-gal4>EGFP-L10a heads relative to total RNA from the starting lysate, and the circadian expression profile, when assayed from total RNA, should approximate the profile in clock cells. Thus, if such an mRNA shows a rhythm by TRAP but not in total RNA, then it is likely to be regulated at the translational level. To identify mRNAs enriched in clock cells, we created new genome-wide libraries for TRAP and total RNA samples from head tissues of tim-uas-gal4>EGFP-L10a–expressing flies. These were sequenced to identify mRNAs that are substantially enriched by TRAP relative to total RNA—that is, enriched in clock cells. We identified many that show an enrichment within clock cells similar to or greater than that observed for tim mRNA. Forty-nine of them are present in our previous list of cycling mRNAs. We chose 12 cycling mRNAs from the enriched list and examined their expression profiles in total RNA versus TRAP RNA samples using Q-PCR methods. Of the 12 mRNAs tested, three did not show cycling similar to that detected by RNA-seq analysis (25%, and the same as we reported for another set of RNAs; Figure S2); thus, these three were not examined further. Of the remaining nine mRNAs, which showed cycling by Q-PCR similar to that detected by RNA-seq, three of them exhibited constant abundance in total RNA but showed circadian cycling in ribosome association, indicating that they are likely regulated at the translational level. Figure 4 shows cycling profiles for these three mRNAs and a fourth mRNA showing both abundance and ribosome-association rhythms (Figure 4D). Thus, for certain mRNAs, there is good evidence for a clock regulation of translation. PPT PowerPoint slide

PowerPoint slide PNG larger image

larger image TIFF original image Download: Figure 4. Comparison of abundance and ribosome-association profiles for several mRNAs. (A–C) Examples of mRNAs that show constant abundance but rhythms in ribosome association. (D) An example of an mRNA showing both abundance and ribosome association rhythms. RNA abundances were normalized to that of Rp49 for each time point. Abundance is expressed relative to that of the first time point (CT0), which was designated a value of 1. Negative and positive error bars show the range of possible relative values calculated based on the SEM of the Ct values obtained in the Q-PCR experiments. Each data point represents a sample size of 6 (3 biological replicates, each with 2 technical replicates). https://doi.org/10.1371/journal.pbio.1001703.g004

Broad Circadian Regulation of Clock Cell Physiology We manually annotated the proteins encoded by the 1,255 cycling RNAs using information obtained from Flybase and classified them by biological process (Figure 5A). Of the annotated genes, the most represented functional class is metabolism/energy production, including NAD-dependent processes and oxidation-reduction reactions. This class includes 85 genes involved in intermediary metabolism, 14 genes with mitochondrial functions, and 46 genes that regulate oxidation-reduction processes. These results are consistent with Drosophila and mouse circadian transcriptional profiling studies that identified a large subset of metabolic genes [33],[34]. Another overrepresented group is signaling (including both intracellular pathways and intercellular signaling mechanisms). Interestingly, 44 members of the signaling class belong to the G Protein signaling family, represented by many G Protein Coupled Receptors (GPCRs) and GTPases. PPT PowerPoint slide

PowerPoint slide PNG larger image

larger image TIFF original image Download: Figure 5. Biological processes represented by the rhythmically translated mRNAs. (A) Pie chart showing different represented processes. The number of mRNAs belonging to each category is shown next to each slice of the pie. (B) Translational profile of thioredoxin system mRNAs. https://doi.org/10.1371/journal.pbio.1001703.g005

Rhythmic Translational Regulation of the NADP+/NADPH Ratio and Cellular Redox State Several particularly interesting cycling mRNAs encode proteins that potentially modulate the NADP+/NADPH ratio or are known components of the cellular redox (thioredoxin) system. Examples include the CG3483 and CG7755 genes, both predicted to encode isocitrate dehydrogenase-like proteins. While at least one isocitrate dehydrogenase (IDH) is a component of the mitochondrial citric acid cycle, others have a cytoplasmic localization, producing αketoglutarate with a conversion of NADP+ to NADPH [35]. We also found that the mRNA encoding Glutathione Transferase E10 (GstE10), which utilizes the redox regulator glutathione in detoxification reactions, exhibits a translational rhythm (Table S4). Interestingly, it was recently shown that glutathione and a different Gst mRNA (GstD1) show circadian changes in abundance in Drosophila head tissues [36], suggesting a complex regulation of redox state. Components of the thioredoxin (TRX) system, a general regulator of cellular redox state, are also under circadian control. Thioredoxin T (TrxT) and Thioredoxin reductase (Trxr-2) mRNAs show robust circadian changes in translation, with peaks in the late subjective day (Figure 5B). This circadian translation may reflect an underlying transcriptional control as both TrxT and Trxr-2 show mRNA abundance rhythms in Drosophila head tissues (Figure S6). Of interest, it was previously suggested that TrxT showed an mRNA abundance rhythm within the Drosophila PDF clock neurons, but this was based only on examination of two circadian times in a screen for cycling mRNAs [10]. Thioredoxin reductases are known to catalyze reduction of thioredoxin, in the process converting NADPH to NADP+ [37], an important regulator of cellular redox. In addition to these TRX system genes, Grx-1, a glutaredoxin also involved with cell redox state homeostasis, shows circadian translational cycling (Table S4). Rhythmicity in cellular redox state is significant as it regulates many biochemical processes including circadian transcription factors (see Discussion).