Response of the Circadian Clock and Diel Starch Turnover to One Day of Low Light or Low CO2

Thiago Alexandre Moraes; Virginie Mengin; Maria Grazia Annunziata; Beatrice Encke; Nicole Krohn; Melanie Höhne; Mark Stitt

doi:10.1104/pp.18.01418

. 2019 Jan 22;179(4):1457–1478. doi: 10.1104/pp.18.01418

Response of the Circadian Clock and Diel Starch Turnover to One Day of Low Light or Low CO₂^¹^,^{^[OPEN]}

Thiago Alexandre Moraes ¹, Virginie Mengin ¹, Maria Grazia Annunziata ¹, Beatrice Encke ¹, Nicole Krohn ¹, Melanie Höhne ¹, Mark Stitt ^1,^2,³

PMCID: PMC6446786 PMID: 30670603

The response of starch accumulation and mobilization to short-term fluctuations in the environment is independent of changes in circadian clock dynamics.

Abstract

Diel starch turnover responds rapidly to changes in the light regime. We investigated if these responses require changes in the temporal dynamics of the circadian clock. Arabidopsis (Arabidopsis thaliana) was grown in a 12-h photoperiod for 19 d, shifted to three different reduced light levels or to low CO₂ for one light period, and returned to growth conditions. The treatments produced widespread changes in clock transcript abundance. However, almost all of the changes were restricted to extreme treatments that led to carbon starvation and were small compared to the magnitude of the circadian oscillation. Changes included repression of EARLY FLOWERNG 4, slower decay of dusk components, and a slight phase delay at the next dawn, possibly due to abrogated Evening Complex function and sustained expression of PHYTOCHROME INTERACTING FACTORs and REVEILLEs during the night. Mobilization of starch in the night occurred in a linear manner and was paced to dawn, both in moderate treatments that did not alter clock transcripts and in extreme treatments that led to severe carbon starvation. We conclude that pacing of starch mobilization to dawn does not require retrograde carbon signaling to the transcriptional clock. On the following day, growth decreased, sugars rose, and starch accumulation was stimulated in low-light-treated plants compared to controls. This adaptive response was marked after moderate treatments and occurred independently of changes in the transcriptional clock. It is probably a time-delayed response to low-C signaling in the preceding 24-h cycle, possibly including changes in PHYTOCHROME INTERACTING FACTOR and REVEILLE expression.

Metabolism and growth are driven by photosynthetic carbon (C) assimilation in the daytime but at night depend on reserves accumulated in previous light periods. The clock plays an important role in regulating diel C allocation and growth (Graf and Smith, 2011; Stitt and Zeeman, 2012; Dodd et al., 2014). Diel regulation is usually studied in repetitive light-dark cycles. In the field, plants experience less predictable events, including day-to-day variation in how much light they receive. Metabolism and growth respond to fluctuating conditions in ways that research in constant environment conditions has failed to uncover, and there is increasing interest in dissecting the role of the clock and other factors in these responses (Nagano et al., 2012; Haydon et al., 2013; Pilkington et al., 2015; Annunziata et al., 2017, 2018; Seki et al., 2017; Frank et al., 2018).

In many plants, the major transitory C reserve is leaf starch (Smith and Stitt, 2007). In recurring light-dark cycles, plants allocate a larger proportion of their fixed C to starch in conditions where less C is available, like short photoperiods or low irradiance (Chatterton and Silvius, 1979, 1980, 1981; Silvius and Snyder, 1979; reviewed by Smith and Stitt, 2007). Arabidopsis (Arabidopsis thaliana) allocates 30%–40% of its photosynthate to starch in long photoperiods, rising to over 60% in short photoperiods (Sulpice et al., 2013; Mengin et al., 2017). At night, starch is degraded in a near-linear manner at a rate such that starch is almost but not completely exhausted at dawn (Graf et al., 2010; Scialdone et al., 2013: Flis et al., 2019). This pattern of mobilization is robust across a wide range of photoperiods and growth irradiances (Gibon et al., 2009; Sulpice et al., 2014; Mengin et al., 2017). Furthermore, it is maintained in the face of changes in irradiance, abrupt changes in the timing of dusk, light-breaks in the night, and night temperature (Smith and Stitt, 2007; Graf et al., 2010; Pyl et al., 2012; Scialdone et al., 2013; Sulpice et al., 2014; Pilkington et al., 2015; Feike et al., 2016; Mengin et al., 2017).

This pattern of diel starch turnover maximizes growth in C-limiting conditions. By reserving a substantial part of the fixed C to support growth in the night, this turnover pattern capitalizes over the entire 24-h cycle on costly investment in growth machinery like the nitrogen and phosphate invested in ribosomes (Piques et al., 2009; Pal et al., 2013). By pacing starch degradation to dawn, it utilizes almost all the fixed C for growth within the 24-h cycle, while avoiding premature exhaustion of starch before the end of the night (Stitt and Zeeman, 2012). The latter would trigger transient C starvation, protein catabolism (Izumi et al., 2013; Ishihara et al., 2015), and an inhibition of growth that extends into the next light period (Gibon et al., 2004b; Yazdanbakhsh et al., 2011; Apelt et al., 2015).

The clock is involved in the regulation of starch turnover (Graf et al., 2010; Scialdone et al., 2013; Pokhilko et al., 2014; Seki et al., 2017; Flis et al., 2019). The Arabidopsis clock can be schematized as an interconnected network of “dawn,” “day,” “dusk,” and “evening” components (Nakamichi, 2011; Pokhilko et al., 2012; Fogelmark and Troein, 2014; Millar, 2016). The 24-h cycle starts with high expression of dawn genes (LATE ELONGATED HYPOCOTYL[ LHY], and CIRCADIAN CLOCK ASSOCIATED1 [CCA1]), followed by day (PSEUDO RESPONSE REGULATOR7, [PRR7], and PRR9), dusk (PRR5, TIME OF CAB EXPRESSION1 [TOC1], and GIGANTEA [GI]), and evening (EARLY FLOWERING3, [ELF3], ELF4, and LUX ARRHYTHMO [LUX]) genes. The day and dusk components repress the dawn genes. Later in the cycle, dusk and evening genes decay or self-repress, allowing LHY and CCA1 to rise to a peak around the next dawn. In addition, many clock components are positively regulated by members of the REVEILLE (RVE) family, in particular, RVE4, RVE6, and RVE8 (Farinas and Mas, 2011; Rawat et al., 2011; Hsu et al., 2013; Shalit-Kaneh et al., 2018). Like other circadian clocks, the plant clock keeps a near-24-h period in the absence of external inputs (Johnson et al., 2003). External inputs like light entrain the internal circadian rhythm to the external light-dark cycle, ensuring that clock outputs occur at an appropriate time. The plant clock is entrained mainly by light at dawn but is also sensitive to the timing of dusk because light modifies the stability and activity of several dusk and evening components (Salomé et al., 2006; Edwards et al., 2010; Kinmonth-Schultz et al., 2013; Staiger et al., 2013; Seo and Mas, 2014; Flis et al., 2016; Oakenfull and Davis, 2017).

Two types of model have been proposed to explain how the clock might regulate starch turnover (Dodd et al., 2014). Both involve clock signaling in combination with information about carbon status or the amount of starch. However, they differ in the way the temporal and metabolic cues are integrated. The arithmetic division (AD) model involves convergence of parallel clock and metabolic signals and proposes that the rate of starch degradation (R) is set by integrating information about the amount of starch (S) and time to dawn (T; i.e. R = S/T; Scialdone et al., 2013). The AD model explains many observations, including robust timing of degradation to the coming dawn in the face of sudden perturbations (see above). However, the molecular identities of S and T are unknown (Seaton et al., 2013; Scialdone and Howard, 2015). T is unlikely to correspond to a classical clock output because the rate of starch degradation can be set and reset between about ZeitgeberTime (ZT) 4 and ZT18 (Graf et al., 2010; Pyl et al., 2012; Scialdone et al., 2013; Sulpice et al., 2014). It has been proposed that T is a semiautonomous variable, which is set by the clock early in the 24-h cycle and decays during the remainder of the cycle (Scialdone et al., 2013; Seaton et al., 2013; Flis et al., 2019). Alternative models have been proposed in which retrograde metabolic signaling modifies clock gene expression and clock phase, which in turn affect starch turnover (termed here RMS models; Feugier and Satake, 2013; Seki et al., 2017). One proposed input involves repression of PRR7 by sugars, leading to downstream changes in CCA1 expression and a 1- to 2-h delay in clock phase (Haydon et al., 2013; Seki et al., 2017). It was recently shown that this input is mediated by bZIP63 (Frank et al., 2018). Another proposed input involves Suc acting via ZEITLUPE to stabilize GI protein (Dalchau et al., 2011; Haydon et al., 2017). There is also evidence that the starvation-signaling component SnRK1/AKIN10 influences phasing of GI and clock period in a TIME FOR COFFEE-dependent manner (Shin et al., 2017). As these inputs act after the event, RMS models do not easily explain the rapid adjustment of starch degradation to abrupt perturbations like an early or late dusk or interruption of the night with a light interval. However, retrograde signaling could potentially facilitate adjustment to preceding changes in light intensity as well as adjustment to sustained changes in the environment.

In natural light environments, a further complication arises as the clock responds to much lower light intensities than those required for rapid photosynthesis. Most phytochrome and cryptochrome signaling is saturated at < 5 µmol m⁻² s⁻¹ (Somers et al., 1998; Devlin and Kay, 2000; Covington et al., 2001; Millar, 2004; Somers, 2005; Salomé et al., 2006). The photosynthetic light compensation point at which gross CO₂ fixation equals the rate of respiratory CO₂ release is between 8 and 40 µmol m⁻² s⁻¹ (Marino et al., 2010), and higher intensities are required for rapid net C fixation. However, some light signaling requires moderate or high irradiance (Mancinelli, 1994; Li et al., 2011; Casal et al., 2014). This is partly because high irradiance speeds photoconversion of phytochrome from the inactive (Pr) to the active (Pfr) form, decreasing the impact of thermal dark reversion on the Pfr/Pr ratio (Trupkin et al., 2014; Legris et al., 2016). Further, some aspects of light signaling are promoted by rising sugars, including Pfr-PHYTOCHROME-INTERACTING FACTOR (PIF)-complex-mediated induction of many light-regulated genes, including some clock components (Shor et al., 2017, 2018). Thus, moderate- or high-fluence light signaling could act as a proxy for the rate of photosynthesis and C status. Indeed, plants might deploy a multitude of mechanisms to cope with complex and often unpredictable environmental changes in the field.

To distinguish between the AD and RMS models, we grew wild-type Arabidopsis plants in a recurring 12-h-light/12-h-dark cycle, challenged them with three different reduced irradiances for one light period, and investigated starch turnover and clock transcript dynamics during the low-light treatment and the following night. The AD model predicts that starch degradation responds to drops in irradiance that do not lead to major changes in clock dynamics, while the RMS model predicts that starch degradation and clock dynamics should show similar responses to a decrease in irradiance. We continued the analyses into the first light period after returning plants to growth conditions to learn if a single low-light day leads to increased allocation to starch in the next light period and if this is independent of or correlates with changes in clock dynamics. We also left plants at growth irradiance but exposed them to low CO₂ for 1 d to distinguish between midfluence light signaling and retrograde C signaling. In all of the treatments, we analyzed additional metabolites and transcripts to put the response of starch and the clock into a broader context.

RESULTS

Gas Exchange, Starch, and Metabolites

Arabidopsis Col-0 was grown at 160 µmol m⁻² s⁻¹ for 19 d and then left at growth irradiance (control) or transferred to 60, 30, or 5 µmol m⁻² s⁻¹ for 12 h (treatment light period), darkened for 12 h (treatment night), and returned to 160 µmol m⁻² s⁻¹ (recovery light period; Supplemental Fig. S1). Photosynthesis decreased to 30% and >10% of the control in 60 and 30 µmol m⁻² s⁻¹ irradiance, respectively, and there was CO₂ release in 5 µmol m⁻² s⁻¹ irradiance (Supplemental Fig. S2). Photosynthesis on the recovery day was similar in all treatments. In a separate experiment, 20-d-old plants were left at 160 µmol m⁻² s⁻¹, exposed to subcompensation point CO₂ (40 μL L^-1) leading to net CO₂ release (Supplemental Fig. S2), and sampled during the light period and following night.

The response of starch and central metabolites is shown in Figure 1 and Supplemental Figure S3 (data provided in Supplemental Table S1). We performed three statistical tests on this and all subsequent data sets. First, at each time point, we asked if low light or low CO₂ had a significant effect using ANOVA with false discovery rate (FDR) correction and Tukey’s honest significance test (HSD) test. The results are shown in Figure 1 and Supplemental Figure S3; for low light, this test interrogated the combined response to all three reduced light intensities. Second, we performed ANOVA with FDR correction and Tukey’s HSD test for each individual treatment and time point (Supplemental Fig. S4A). This was done to detect changes at a limited number of time points. Third, we grouped time points, calculated the response (treatment value as a fraction of the control value; Supplemental Equation S1) at each time, averaged the values across the time interval, and tested the values in the time interval for significance using one-sample t tests with FDR correction (Supplemental Fig. S4B). We defined three time intervals corresponding to the treatment light period (ZT2–12), the following night (ZT14–24), and the last part of the recovery light period (ZT6–12 in the following light period; earlier times were excluded because they might be influenced by values at the end of the night). The latter two analyses are summarized in Figure 2A, which shows the average response in each time interval and indicates if the response was significant (P value < 0.05 with FDR) for at least one time point within the time interval.

Figure 2. — Starch, metabolites, and C reporter transcripts: statistical analyses and response profiles. A, Starch and metabolite levels. This summarizes the responses and statistical analyses shown in Figure 1 and Supplemental Figures S3 and S4. It provides a condensed visualization of the magnitude of the change to a decrease in irradiance or a decrease in CO₂ relative to control plants left in growth conditions, termed a response profile. Separate response profiles are shown for three time intervals: the treatment light period (ZT2–ZT12), the treatment night (ZT14–ZT24), and the recovery light period (ZT6–ZT12 in the recovery light period [indicated as (a), (b), and (c) under each column]; the first two time points in the recovery light period were excluded because the value at the end of the night often differed from the control, and this influenced the values in the first 2–4 h after returning to growth irradiance). In the figure, the time axis shows the time in hours after the start of the treatments. The response profile for metabolites shows the response in a given treatment (calculated as treatment/control; Supplemental Equation S1A) at each time and then averaged over all points in the time interval (as in Supplemental Fig. S4B). Treatments are indicated by color: control (yellow = 0); 60, 30, and 5 µmol m⁻² s⁻¹ reduced irradiance (orange, red, and dark red); and 40 μL L^-1 CO₂ (blue). To visualize small and large changes on a common scale, the response profiles are plotted on a logarithmic axis (control value = 1, range from 0.006 to 4.63, with values under 1 denoting a decrease in the treatment compared to the control and values over 1 denoting an increase in the treatment compared to the control). The statistical significance of the response in each time interval compared to the control is indicated by the symbols (open symbol, not significant; solid symbols, P values ≤ 0.05 with FDR correction for at least one time point in the time interval; cases where significant differences were rejected by the Tukey’s HSD posttest are indicated as not significant; see Supplemental Fig. S4A for details). B, Carbon reporter transcripts. This display summarizes the analyses in Supplemental Figs. S6 and S7. Analyses were performed as in A, except that, as the calculation started with log₂ values, the response to a given treatment was calculated as 2^[log₂(treatment) − log₂(control)]; Supplemental Equation S1B) before averaging them across all times in a given time interval (for details see Supplemental Fig. S7B). The response profiles are shown on a logarithmic axis (control value = 1, range from 0.06 to 779.7). The color code is as in A. The statistical significance of the response in each time interval compared to the control is indicated by the symbols (open symbol, not significant; solid symbols, P values ≤ 0.05 with FDR correction for at least one time point in the time interval; cases where significant differences were rejected by the Tukey’s HSD posttest are indicated as not significant; see Supplemental Fig. S7A for details).

Compared to the control, starch accumulation was slowed to 42% and 16% in 60 and 30 µmol m⁻² s⁻¹ irradiance, respectively, and abolished in 5 µmol m⁻² s⁻¹ irradiance or 40 μL L^-1CO₂ (Figs. 1, A and B, and 2A; already significant in the most moderate light treatment). At night, starch was mobilized in a near-linear manner. The degradation rate was calculated by linear regression between ZT12 and ZT22. Compared to the control, degradation was significantly slower after illumination at 60 and 30 µmol m⁻² s⁻¹ (5.64 µmol C g⁻¹ fresh weight [FW] h⁻¹ 95% CI 6.13–5.15, 2.54 µmol C g⁻¹FW h⁻¹ 95% CI 2.82–2.25, and 0.98 µmol C g⁻¹FW h⁻¹ 95% CI 1.05–0.91, respectively). When extrapolated, these rates would exhaust starch at 24.0, 23.2, and 23.9 h, respectively, after the previous dawn.

On the recovery day, the rate of starch accumulation, relative to the control, increased by 29%, 41%, and 39% after decreasing irradiance to 60, 30, and 5 µmol m⁻² s⁻¹, respectively, in the previous light period (significant after the most moderate treatment; Figs. 1A and 2A). The rate of accumulation in the control on the recovery day resembled that on the treatment day.

Reduced irradiance led to a progressive decrease in sucrose (Suc; Fig. 1, C and D), glucose (Glc; Fig. 1, E and F), fructose (Fru; Supplemental Fig. S3, A and B), Glc6P (Supplemental Fig. S3, C and D), malate, and fumarate (Supplemental Fig. S3,E–H) in the treatment light period and the following night (Fig. 2A). Most changes were significant, either at individual times or in the grouped analyses (Supplemental Fig. S9). The responses to low CO₂ resembled those in 5 µmol m⁻² s⁻¹ irradiance. Amino acids showed a complex response (Supplemental Figs. S3, I and J, and S4). At 60 and 30 µmol m⁻² s⁻¹, amino acids were lower than the control during the treatment light period and night. At 5 µmol m⁻² s⁻¹ and 40 μL L^-1 CO₂, they were almost as high as the control in the light and higher than the control in the night; this may reflect protein catabolism under C starvation (Caldana et al., 2011; Izumi et al., 2013; Ishihara et al., 2015).

On the recovery day, many metabolites were significantly higher than in the control (Figs. 1 and 2A; Supplemental Figs. S3 and S4). Glc and Fru showed a 3- to 4-fold increase in the 60 µmol m⁻² s⁻¹ treatment and a slightly larger increase in the 30 and 5 µmol m⁻² s⁻¹ treatments (Fig. 1E; Supplemental Fig. S4A). The increase was significant at individual times for Glc and Fru in the 60 µmol m⁻² s⁻¹ treatment (Supplemental Fig. S4A) and in the grouped analyses for Glc in the 60 µmol m⁻² s⁻¹ and for Fru in the 30 µmol m⁻² s⁻¹ treatment (Supplemental Fig. S4B).

C Status Estimated by Integrated Analysis of Metabolite Levels

We used a principal component (PC)-analysis-based approach to compare C status across treatments and times. PC analysis was performed on a z-score normalized data set for all metabolites, treatments, and times (Supplemental Fig. S5). As a reference, we included samples harvested after darkening for 24 h to generate extreme C starvation. In PC1 (66% of total variance), the C starvation reference samples grouped at the negative end of the axis; the 5 µmol m⁻² s⁻¹ and low-CO₂ samples grouped near the starvation references; the 30, 60, and 160 µmol m⁻² s⁻¹ samples showed increasingly positive scores; and recovery-day samples from low-light treatments showed the most positive scores. PC2 (15% of variation) separated samples with high amino acids. We used the PC plot to calculate the Euclidean distance between each individual sample and the average of the C starvation reference samples. This distance, which we term the “C status score,” integrates information from the entire metabolite data set (Fig. 1G). In the control, the C status score rose during the light period and declined at night. The 60, 30, and 5 µmol m⁻² s⁻¹ treatments showed a progressive decrease in the C status score, and the low CO₂ treatment showed an even lower score than the 5 µmol m⁻² s⁻¹ treatment. On the recovery day, the low irradiance treatments showed a higher C status score than the control.

C Status Estimated by the Abundance of C-Responsive Transcripts

To test whether our treatments led to transcriptional changes through C signaling, we investigated five transcripts that are known to respond to C status (Usadel et al., 2008; Cookson et al., 2016). These included three genes that are induced (BCAT2/At1g10070, DIN1/At4g35770, and DIN6/At3g47340) and two that are repressed (Cpn60alpha/At2g28000 and Asp.P/At5g07030) in C starvation. In these and all other analyses of transcript abundance, we spiked six RNA species into the plant material before RNA extraction and cDNA preparation and used these to calibrate the reverse transcription quantitative PCR analysis. This allowed us to determine absolute transcript abundance (copy number.cell⁻¹; Flis et al., 2015, 2016). This and all following transcript time series were statistically analyzed using the approach described for metabolites. The results are compiled in Figure 2B (see Supplemental Fig. S6 for the data and Supplemental Fig. S7 for statistical analyses).

There were significant changes in transcript abundance for DIN1, DIN6, and Cpn60alpha when irradiance was decreased to 60 µmol m⁻² s⁻¹, for BCAT when irradiance was decreased to 30 µmol m⁻² s⁻¹, and for Asp.P when irradiance was decreased to 5 µmol m⁻² s⁻¹. This reveals that low-C signaling is triggered by a moderate treatment that still permits some starch accumulation and growth and becomes progressively stronger in lower irradiance or low CO₂. On the recovery day, transcript abundance reverted within 4 h to control-like values, except for a small residual increment for DIN1 and DIN6 and a slight diminution for Cpn60alpha in the 5 µmol m⁻² s⁻¹ treatment.

Estimation of Growth Rates Using a Whole-Plant C Model

We used our measurements of photosynthesis, respiration, and metabolite levels to estimate how quickly C is deposited in structural biomass, using a whole-plant C balance model (Supplemental Table S1; see Sulpice et al., 2014; Flis et al., 2016; Mengin et al., 2017). Briefly, C in measured metabolites was summed at each time point, and the change in summed C calculated for each 2-h time interval (ΔC). The rate of deposition of C in structural biomass in the light and at night was then estimated as A − ΔC and ΔC − R, where A and R are the rates of photosynthesis and respiration. The calculation ignores C reserves in the roots, which are negligible in Arabidopsis (Yazdanbakhsh et al., 2011). Figure 1H shows averaged rates for the treatment light period, the treatment night, and the recovery light period. Negative values indicate that catabolism is occurring to support maintenance.

In control plants, the estimated growth rate was similar in the treatment light period and the recovery light period, and 4-fold lower at night (Sulpice et al., 2014; Flis et al., 2016; Mengin et al., 2017). Plants subjected to the 60 µmol m⁻² s⁻¹ treatment grew at about 30% of the control rate in the treatment light period and exhibited slightly negative growth in the night. Plants subjected to the 30 µmol m⁻² s⁻¹ treatment exhibited slightly negative growth in the treatment light period and strongly negative growth in the night. The 5 µmol m⁻² s⁻¹ and low-CO₂ treatments showed negative growth in the treatment light period and night. In the recovery light period, plants previously subjected to reduced irradiance had 18%–40% lower estimated growth rates than the control (significant at P < 0.05 or < 0.01).

In summary, first, 60 µmol m⁻² s⁻¹ irradiance led to a restricted C supply in the light period and mild C starvation at night, 30 µmol m⁻² s⁻¹ led to mild C starvation in the light period and stronger C starvation at night, and 5 µmol m⁻² s⁻¹ or 40 μL L^-1 CO₂ led to severe C starvation throughout the light period and night. This was accompanied by increasingly strong transcriptional responses. Second, moderate changes in irradiance led to slower starch degradation in the following night and to slower growth and faster starch accumulation in the following light period. Third, starch mobilization was paced to dawn, even when plants were starving.

Clock Transcripts

We investigated transcript abundance for 10 core clock genes (Figs. 3, 4, and 5; Supplemental Fig. S8; see Supplemental Fig. S9 for significance tests and Supplemental Table S2 for data and estimation of amplitude and peak timing). Decreasing irradiance to 60 or 30 µmol m⁻² s⁻¹ produced few significant or consistent changes in clock transcript abundance relative to the control. Reduction to 5 µmol m⁻² s⁻¹ led to widespread but mainly small changes. Low CO₂ mimicked most of the changes in the 5 µmol m⁻² s⁻¹ treatment; differences may indicate differential responses to light and C or interexperiment variation.

Figure 3. — Clock transcript abundance: temporal dynamics. Transcripts were measured in the experiments described in Figure 1, with either a decrease in light intensity from 160 to 60, 30, or 5 µmol m⁻² s⁻¹ irradiance for one light period (A, C, E, G, I, and K) or a decrease in CO₂ from about 400 to 40 μL L^-1 (B, D, F, H, J, and L). Triplicate samples were collected in control plants left in growth conditions and in each treatment (see figure for symbols) at 2-h intervals to measure (A and B) *LHY*, (C and D) *PRR7*, (E and F) *TOC1*, (G and H) GI, (I and J) *LUX*, and (K and L) *ELF4*. Results are shown as mean ± 95% confidence interval. Statistical significance of the combined response at each time point by ANOVA, Benjamini and Hochberg FDR, and Tukey’s HSD posttest is as in Figure 1. Data are provided in Supplemental Table S2, experimental design is in shown in Supplemental Figure S1, other clock transcripts are in Supplemental Figure S8, statistical analyses of responses to individual treatments are in Supplemental Figure S9, a compilation of the statistical analyses and the response profiles are in Figure 4, and estimates of the timing of peak transcript abundance are in Figure 5A.

Figure 4. — Clock transcript abundance: compiled statistical analyses and response profiles. Summary of the data shown in Figure 2 and Supplemental Figure S8 and the data analyses in Supplemental Figure S9. Analyses were performed as described in Figure 2B, with the response profile being plotted on a logarithmic axis (from 0.23 to 5.59). The statistical significance of the response in each time interval compared to the control is indicated by the symbols (open symbol, not significant; solid symbols, P values ≤ 0.05 with FDR correction for at least one time point in the time interval; cases where significant differences were rejected by the Tukey’s HSD posttest are indicated as not significant; see Supplemental Fig. S9A for details). The underlying data are given in Supplemental Table S2, the experimental design in Supplemental Figure S1, the temporal dynamics of clock transcripts in Figure 3 and Supplemental Figure S9, and phase analysis in Figure 5.

Figure 5. — Estimated peak times for clock, *GBSS1*, *PIF*, and *RVE* transcript abundance. A, Clock genes; B, GBSS1; C, selected PIF family members; and D, selected RVE family members. The underlying data are provided in Supplemental Table S2, and the temporal dynamics of transcript abundance are shown in Figures 3, 6, and 7 and Supplemental Figures 8, 11, and 13. Timing of peak abundance is defined as the inflection point of a transcript time series, which is preceded by rising transcript levels and succeeded by declining transcript levels and is calculated based on the average timing of peak of the bootstrapped time series (symbols) using both polynomial fit and spline smooth (B = 15 for each method). Error bars represent the 95% confidence interval of the bootstrap results; different letters indicate statistically different peak times (Tukey’s HSD, alpha = 0.001). Colors indicate different low-light treatments. Low CO₂ estimates are not available due to no samples being taken in the recovery light period.

For LHY and CCA1 transcripts, reduced irradiance led to slightly slower decay, lower abundance at the trough during the night (Fig. 3A; Supplemental Fig. S8A; significant in individual analyses for LHY in the 30 and 5 µmol m⁻² s⁻¹ treatments, and in grouped analyses for LHY at all irradiances and CCA1 at 5 µmol m⁻² s⁻¹, see Fig. 4; Supplemental Fig. S9), and delayed peak time at the next dawn by up to 2 h (Fig. 5A; significant for LHY and CCA1 in the 30 and 5 µmol m⁻² s⁻¹ treatments). Low CO₂ significantly delayed the rise of LHY and CCA1 transcripts at the following dawn (Fig. 3B; Supplemental Fig. S8B).

The PRR7 transcript showed a small nonsignificant increase in its peak value at 5 µmol m⁻² s⁻¹ and even smaller and inconsistent changes at 30 or 60 µmol m⁻² s⁻¹ (Fig. 3C; Supplemental Fig. S9). Low CO₂ led to a significant 2-fold increase in peak PRR7 transcript abundance (Figs. 3D and 4; Supplemental Fig. S9). This is consistent with the earlier report that PRR7 is induced by low C (Haydon et al., 2013; Frank et al., 2018) but reveals that the response requires extreme C starvation. At night, PRR9 and PRR7 showed up to 4-fold elevated levels around their trough in the 5 µmol m⁻² s⁻¹ treatment (significant for PRR9 at individual time points and for PRR9 and PRR7 in the grouped analysis; Fig. 4; Supplemental Fig. S9), but not in the 30 or 60 µmol m⁻² s⁻¹ treatments, and showed inconsistent responses in the low CO₂ treatment.

GI transcript dynamics showed two small modifications (Fig. 3G). First, low light attenuated a secondary peak at ZT2 (Fig. 4; significant effect at 5 µmol m⁻² s⁻¹ for individual time points, see Supplemental Fig. S9). Second, the decline after ZT12 was slightly delayed in the 5 µmol m⁻² s⁻¹ treatment (Fig. 3G, significant in the grouped analysis; Supplemental Fig. S9B). The changes in low CO₂ were inconsistent (Figs. 3H and 4; Supplemental Fig. S9).

PRR5 and TOC1 transcript rose significantly faster in the light period in 5 µmol m⁻² s⁻¹ irradiance and in low CO₂ (Figs. 3, E and F, and 4; Supplemental Figs. S8, E and F, and S9). This response was very weak or nonperceptible at 30 and 60 µmol m⁻² s⁻¹. They also showed a modified response during the night. In the control, PRR5 and TOC1 transcript declined, rose to minor secondary peak at ∼ZT20, and then declined. This secondary peak has been reported before (see “Discussion”). In the 5 µmol m⁻² s⁻¹ and low-CO₂ treatments, the initial decline weakened, resulting in a broad plateau during the night and significantly higher (Supplemental Fig. S9) transcript abundance at dawn. These responses were not apparent in the 30 and 60 µmol m⁻² s⁻¹ treatments.

Among the evening genes, LUX (Figs. 3, I and J, and 4) showed a weak response. ELF3 showed slightly higher expression around its trough at ZT0 to 2 in low CO₂ and a similar but nonsignificant trend at 5 µmol m⁻² s⁻¹ (Fig. 4; Supplemental Figs S8, G and H, and S9). ELF4 showed a strong response to 5 µmol m⁻² s⁻¹ and low CO₂, with a delay until the transcript rose, about 2-fold lower peak levels, and lower levels during most of the night (Fig. 3, K and L). The response during the night was significant in the 30 and 60 µmol m⁻² s⁻¹ treatments, both at individual times and in grouped analyses (Fig. 4; Supplemental Fig. S9). These results point to ELF4 being repressed by low C in a range relevant for clock operation. Decreased ELF4 expression may abrogate evening complex (EC) activity (see “Discussion”).

GRANULE BOUND STARCH SYNTHASE1

We also analyzed transcripts for the dawn marker GRANULE BOUND STARCH SYNTHASE1 (GBSS1). GBSS1 is responsible for amylose synthesis during starch granule formation (Martin and Smith, 1995). In the control, GBSS1 transcript was high at dawn, rose to a peak at about ZT2, declined to a trough at about ZT16, and then rose (Fig. 6). Low light prevented the rise between ZT0 and ZT2, delayed the subsequent decline and recovery, and delayed peak time at the following dawn by about 2 h (Fig. 5B). Many of these changes, including the delayed peak time at the following dawn, were significant in the 60 µmol m⁻² s⁻¹ treatment and became stronger in the 30 and 5 µmol m⁻² s⁻¹ treatments (Fig. 5B; Supplemental Fig. S9).

Figure 6. — *GBSS1* transcript abundance and response profile. A, Transcript abundance. Transcripts were measured in the experiments described in Figure 1, with either a decrease in light intensity from 160 to 60, 30, or 5 µmol m⁻² s⁻¹ irradiance for one light period. Triplicate samples were collected in control plants left in growth conditions and in each treatment (see figure for symbols) at 2-h intervals. Data are provided in Supplemental Table S2, experimental design is in shown in Supplemental Figure S1, and statistical analyses of responses to individual treatments are in Supplemental Figure S9. Results are shown as mean ± 95% confidence interval, statistical significance of the combined response at each time point by ANOVA, Benjamini and Hochberg FDR, and HSD Tukey’s posttests as in Figure 1. B, Response profile summarizing the responses shown in Figure 6A and the data analyses in Supplemental Figure S9. Analyses were performed as described in Figure 2B, with the response profile being plotted on a logarithmic axis (from 0.23 to 5.59) The statistical significance of the response in each time interval compared to the control is indicated by the symbols (open symbol, not significant; solid symbols for P values ≤ 0.05 with FDR correction for at least one time point in the time interval; cases where significant differences were rejected by the Tukey’s HSD posttest are indicated as not significant; see Supplemental Fig. S4A for details of the calculations and Supplemental Fig. S9A for the calculated values for the responses and P values).

PIF Family Members

We investigated two other gene families that are implicated as clock inputs and outputs. PIF family members show a strong circadian rhythm in transcript abundance due to repression by EC (Nusinow et al., 2011). The response to our treatment could indicate whether low light or C abrogate EC function. Low irradiance altered the diel rhythm of many PIF transcripts (Fig. 7; Supplemental Fig. S10; see Supplemental Fig. S11 for statistical analyses).

Figure 7. — *PIF4* and *PIF5* transcript abundance and compiled statistical analyses and response profiles. A to D, Transcript abundance. Transcripts were measured in the experiments described in Figure 1, with either a decrease in light intensity from 160 to 60, 30, or 5 µmol m⁻² s⁻¹ irradiance for one light period (A and C) or a decrease in CO₂ from about 400 to 40 μL L^-1 (B and D). Triplicate samples were collected in control plants left in growth conditions and in each treatment (see figure for symbols) at 2-h intervals to measure (A and B) *PIF4* and (C and D) *PIF5*. Results are shown as mean ± 95% confidence interval. Statistical significance of the combined response at each time point by ANOVA, Benjamini and Hochberg FDR, and Tukey’s HSD posttest was performed and is shown as in Figure 1. E, Response profiles. Analyses were performed on the data in A and B as described in Figure 2B. The response profile is plotted on a logarithmic axis (from 0.37 to 19.47). The statistical significance of the response in each time interval compared to the control is indicated by the symbols (open symbol, not significant; solid symbols for P values ≤ 0.05 with FDR correction for at least one time point in the time interval; cases where significant differences were rejected by the Tukey’s HSD posttest are indicated as not significant; see Supplemental Fig. S4A for details of the calculation and Supplemental Fig. S11 for the calculated values for the responses and P values).

PIF4 showed a particularly strong response (Fig. 7, A, B and E; Supplemental Figure S11). In the control treatment, the PIF4 transcript declined late in the light period and at night. This decline was significantly attenuated in the 60 µmol m⁻² s⁻¹ treatment and further attenuated in the 30 and 5 µmol m⁻² s⁻¹ treatments and the low CO₂ treatment. PIF5 transcript showed a similar and significant response in the 5 µmol m⁻² s⁻¹ treatment, but not in moderate light treatments or low CO₂ (Fig. 7, C–E; Supplemental Fig. S11). Low light consistently delayed peak time for PIF4 but not PIF5 (Fig. 5C). These results indicate that low light attenuates the decline of PIF4 and, to a lesser extent, PIF5 transcripts and that this action is at least partly due to low C.

Low light slightly attenuated the decline of PIF3 transcript during the following night (significant at 5 µmol m⁻² s⁻¹ in the grouped analysis; Supplemental Fig. S11B), accentuated the decline of PIF6 and PIF7 transcript (significant at 5 µmol m⁻² s⁻¹ in individual and grouped analyses; Supplemental Figs. S10 and S11), and led to a 2.5-h delay in PIF7 peak time (Fig. 5C). Some of these responses were significant in the 60 or 30 µmol m⁻² s⁻¹ treatments (Supplemental Fig. S11).

RVE Family Members

RVE4, RVE6, and RVE8 act antagonistically to LHY and CCA1 as partly redundant positive regulators of many clock genes (Shalit-Kaneh et al., 2018) by binding to evening element motifs to induce dusk and evening components like PRR5, TOC1, ELF4, and LUX, as well as the morning-phased PRR9 (Farinas and Mas, 2011; Rawat et al., 2011; Hsu et al., 2013; Gray et al., 2017). In the control, RVE4 transcript showed a diel oscillation with a trough at about ZT10. This oscillation was almost abolished in 5 µmol m⁻² s⁻¹ or low-CO₂ conditions (Fig. 8, A and B, significant at individual times and in the grouped analysis; Supplemental Fig. S13, A and B) and was attenuated in the 60 and 30 µmol m⁻² s⁻¹ treatments (significant in the grouped analyses; Supplemental Fig. S13B). RVE6 and RVE8 transcript abundance did not show a consistent response to reduced irradiance but showed a slight though significant increase in low CO₂ (Fig. 8, C and D; Supplemental Fig. S13). In control plants, the peak value for RVE4 transcript abundance was 8- and 16-fold higher than that of RVE8 and RVE6, respectively. The 5-fold increase in the RVE6 trough value in low irradiance or low CO₂ therefore represents a substantial increase in total RVE4 plus RVE6 plus REV8 transcript in the middle of the 24-h cycle.

Figure 8. — *RVE4*, *RVE6*, and *RVE8* transcript abundance: temporal dynamics and compilation of statistical analyses and response profiles. A to F, Transcript abundance. Transcripts were measured in the experiments described in Figure 1, with either a decrease in light intensity from 160 to 60, 30, or 5 µmol m⁻² s⁻¹ irradiance for one light period (A, C, and E) or a decrease in CO₂ from about 400 to 40 μL L^-1 (B, D, and F). Triplicate samples were collected in control plants left in growth conditions and in each treatment (see figure for symbols) at 2-h intervals to measure (A and B) *RVE4*, (C and D) *RVE6*, and (E and F) *RVE8*. Results are shown as mean ± 95% confidence interval. Statistical significance of the combined response at each time point by ANOVA, Benjamini and Hochberg FDR, and Tukey’s HSD posttest was performed and is shown as in Figure 1. G, Response profiles. Analyses were performed on the data in A to F as described in Figure 2B. The response profile is plotted on a logarithmic axis (from 0.25 to 14.87). The statistical significance of the response in each time interval compared to the control is indicated by the symbols (open symbol, not significant; solid symbols, P values ≤ 0.05 with FDR correction for at least one time point in the time interval; cases where significant differences were rejected by the Tukey’s HSD posttest are indicated as not significant; see Supplemental Fig. S4A for details of the calculation and Supplemental Fig. S13 for the calculated values for the responses and P values).

RVE1, RVE2/CIR1, and RVE7/EPR1 are implicated as clock outputs (Zhang et al., 2007; Rawat et al., 2009). The diel rhythm of RVE1 transcript was attenuated (significant for 5 µmol m⁻² s⁻¹ and low CO₂ at individual times, and for all treatments in the grouped analysis; Supplemental Figs. S12, A and B, and S13). The decline and recovery of RVE2 and RVE3 transcript were delayed in the 5 µmol m⁻² s⁻¹ treatment (significant for RVE2 and RVE3 at individual times and for RVE3 in the grouped analysis; Supplemental Fig. S12, C–E, and S13). The decline of RVE7 transcript was attenuated in 5 µmol m⁻² s⁻¹ and low CO₂ (significant at individual times and in the grouped analysis; Supplemental Figure S12, I and J, and S13).

Overview of the Light and C Responsiveness of Clock, PIF, and RVE Transcripts

Figure 9 provides three comparative analyses of the response of clock and clock-associated transcripts to low irradiance or low CO₂. Responses are shown for three sets of genes: core clock transcripts represented in the model of Pokhilko et al. (2012), members of the PIF gene family, and members of the RVE gene family, which includes not only clock outputs but also positively acting clock components (see above). Figure 9A compares the responses of these transcripts with those of C reporter transcripts. To do this, we used the averaged ratio across the three consecutive time points with the largest difference from controls. Although some clock genes (LHY and PRR9) and members of the PIF (especially PIF4) and RVE (especially RVE1, RVE7, and the clock component RVE4) families respond quite strongly (up to 4-fold changes), their responses are far smaller than the C reporter transcripts. It should also be noted that the strongest response often occurred near the trough when transcript abundance was very low (e.g. for LHY, PRR9, PRR7, and PRR5). Altered abundance at the trough points to changes in upstream regulators but is unlikely to affect clock outputs, i.e. regulate downstream targets.

Figure 9B compares the response to low irradiance or low CO₂ (calculated as in Fig. 9A) with the diel oscillation in transcript abundance. For clock transcripts, decreasing the irradiance to 60 or 30 µmol m⁻² s⁻¹ led to only small changes (<10%) compared to the diel oscillation. Extreme treatments (5 µmol m⁻² s⁻¹ irradiance, 40 μL L^-1 CO₂) led to larger changes for TOC1 transcript (∼35% of the diel oscillation) and changes of up to ∼25% for PRR9, PRR7, and ELF3 and ∼20% for PRR5, LUX, ELF4, and ELF3. The high values for TOC1 and ELF3 in part reflect their relatively small diel oscillation. The dawn output of GBSS1 showed a small response (<25%) relative to its diel oscillation. PIF and RVE transcripts tended to show larger responses relative to their diel change. Many showed substantial responses at 60 or 30 µmol m⁻² s⁻¹ (e.g. PIF1, PIF3, PIF4, RVE1, RVE4, and RVE6) and responses to 5 µmol m⁻² s⁻¹ or low CO₂ that were > 50% of their diel oscillation (e.g. PIF2/PIL1, PIF3, PIF4, RVE4, and RVE7). In summary, moderate C depletion has little effect on most clock transcripts but a stronger impact on some positively acting RVE clock components and several output transcripts.

In Figure 9C, the transcript data set is analyzed using an analogous approach to that used to estimate the C status score (Fig. 1G). PC analysis was performed on z-score normalized data for all transcripts, irradiance treatments, and times. Using a plot of PC1 against PC2, the Euclidean distance was then calculated between each individual sample and a reference, which in this case was the average of all time points in the control 160 µmol m⁻² s⁻¹ treatment. This distance, which we term the “transcript response score,” integrates and visualizes the response of a set of transcripts. The analysis was performed separately for the three sets of transcripts. For clock genes defined in the model of Pokhilko et al. (2012), the transcript response score in the control (160 µmol m⁻² s⁻¹) treatment changes between ZT0 and ZT2, diverges further until ZT8 to 10, and then gradually reverts to the ZT0 value. This reflects the progressive decrease of dawn and rise of day, dusk, and evening transcript in the first part of the 24-h cycle and the reversal of this process in the second part of the cycle. The response in the 60 and 30 µmol m⁻² s⁻¹ treatments resembles the control. The response in the 5 µmol m⁻² s⁻¹ treatment resembles the control except for nonsignificant divergence at ZT18 and ZT22 and significant divergence at ZT24. The PIF gene set showed marked changes after dark-light and light-dark transitions but did not show consistent changes between irradiance treatments. This may be because PIF family members show diverse responses to low irradiance (Fig. 8; Supplemental Figs. S11 and S12). The RVE transcript set diverged from the ZT0 value in the first part of the 24-h cycle and reverted during the night. This response was consistently and at several time points significantly damped in the 5 µmol m⁻² s⁻¹ treatment and weakly damped at some times in the 30 µmol m⁻² s⁻¹ treatment. This reflects damping of the diel oscillation of several RVE family members in low irradiance (Fig. 9; Supplemental Figs. S12 and S13), including RVE4, which acts antagonistically to LHY and CCA1 to positively regulate many core clock genes, as well as RVE1, RVE3, and RVE7, which more likely act as clock outputs (see above). Overall, this analysis reiterates that, whereas metabolism responds strongly to a moderate decrease in irradiance (Fig. 1G), most core clock transcripts only respond to an extreme decrease in irradiance.

Comparison to Public Data on the Response of Clock, PIF, and RVE Transcripts to C

Finally, we inspected the responses of clock, PIF, and RVE transcripts to C in a compilation of low-C treatments (Usadel et al., 2008). These included (1) removal and resupply of Suc to Col-0 seedlings in liquid culture in continuous low light, (2) illumination of vegetatively growing Col-0 for 4 h after dawn at ambient or subcompensation point CO₂, and (3) diel time series for Col-0 and the starchless pgm mutant. The latter allowed separate assessment of the response to high sugar in the light period and low sugar at night. The results are summarized in Figure 10 (see Supplemental Text S2 for a description of the treatments and Supplemental Figs. S14–S16 for replots of the data).

Figure 10. — Meta-analysis of published responses to C and comparison with the response to low irradiance or low CO₂. Summary of the analysis of a published data compilation (Usadel et al., 2008) that includes multiple C treatments: (1) removal and resupply of Suc to 7-d-old Col-0 seedlings in liquid culture in continuous very low (20 µmol m⁻² s⁻¹) light; (2) illumination of 35-d-old vegetatively growing Col-0 at dawn for 4 h in the presence of ambient or subcompensation point CO₂; and (3) comparison of diurnal time series for 35-d-old Col-0 and the starchless *pgm* mutant in a 12-h photoperiod (160 µmol m⁻² s⁻¹). As the *pgm* mutant has high sugars in the light period and low sugars at night, the latter treatment also allowed us to separately assess the response of transcript abundance and peak time to high sugar in the light period and to low sugar at night. See legend of Supplemental Figure S14 for more details and Supplemental Figures S14–S16 for data displays. A, The data from Usadel et al. (2008) were analyzed to detect whether low C consistently led to an increase (orange) or decrease (blue) in transcript abundance (left hand side of the display). For comparison, A also summarizes whether transcript abundance increased (red) or decreased (blue) in the one light period of low irradiance or low CO₂ treatments (Figs. 2–8). B, Time-resolved plots of diurnal changes of transcript abundance in wild-type Col-0 versus *pgm* were analyzed to detect whether the low-sugar night in *pgm* was associated with a delay (yellow) or advance (green) in peak transcript abundance of dawn-phased genes (*LHY*, *CCA1*, *PRR9*, and *PRR7*) and whether the decline of transcript for dusk-phased genes (*PRR5*, *TOC1*, GI, *LUX*, and *ELF4*) slowed down, leading to a weakening of the trough between the major and minor peaks as well as higher dawn levels of these transcripts. Responses after a single day of low irradiance or low CO₂ are also included for comparison.

This meta-analysis provided independent support for conclusions drawn from Figures 3–9. A plentiful C supply consistently repressed PRR9, PRR7, PRR5, TOC1, GI, and ELF3. The clear signature for PRR7 is in agreement with a report that this gene is repressed by C (Haydon et al., 2013). However, in line with Figures 3–5 and 9, the responses to C were very small compared to the diel oscillation. Peak times for LHY, CCA1, and TOC1 were slightly delayed in pgm compared to Col-0, recapitulating the delayed peak after a day in low irradiance or low CO₂ (Fig. 3). The decline of PRR5, TOC1, and LUX transcript early in the night was slower in pgm than Col-0 wild type. These results imply that low C at night is responsible for the slow decline of PRR5, TOC1, and LUX transcripts in the night and the delay in LHY and CCA1 peak time on the recovery day after a day at low irradiance or low CO₂. The meta-analysis also confirmed that C represses PIF4 and PIF5. Further, C consistently repressed members of the RVE gene family.

DISCUSSION

We simulated natural day-to-day fluctuations in irradiance by subjecting plants to 1 d of decreased irradiance and returning them to growth irradiance. We also subjected plants to low CO₂ to distinguish between responses triggered by midfluence light signaling and C signaling. Diel starch turnover responded to small decreases in irradiance. First, reduced irradiance led to slower starch mobilization in the following night, with the rate being reset such that reserves lasted until dawn. This pattern was maintained in the face of severe C starvation, revealing that mobilization is paced to dawn by a network that is impervious to short-term retrograde C-starvation signals. Second, starch accumulation increased in response to a moderate decrease in irradiance in the previous light period. The sensitive response of diel starch turnover contrasted with clock transcripts, which showed few significant responses to moderate decreases in irradiance. This recapitulates the robust clock dynamics seen in earlier studies (Flis et al., 2015). The finding that diel starch turnover responds to changes in irradiance and C availability independently of changes in clock dynamics is consistent with the AD model, where clock and metabolic signals act parallel. It is inconsistent with RMS models, where retrograde metabolic signals modify clock dynamics, which in turn modify starch turnover.

Pacing of Starch Mobilization to Dawn Does Not Require Modification of Clock Dynamics

As in previous studies (see “Introduction”), starch degradation was paced to dawn, irrespective of short-term changes in the dusk starch content. In the AD model proposed by Scialdone et al. (2013), the clock sets a maximum rate of starch degradation such that starch reserves last until dawn. RMS models propose that degradation is regulated by modifications in clock dynamics, which are brought about by changes in sugar levels (Feugier and Satake, 2013; Seki et al., 2017), including induction of PRR7 under C starvation (Haydon et al., 2013; Seki et al., 2017). Our results show that the regulatory network that paces starch degradation to dawn does not involve changes in clock dynamics and is impervious to short-term signals deriving from C starvation. This is consistent with the AD model and incompatible with the idea that starch mobilization is regulated by changes in clock gene expression or phase.

In the 60 µmol m⁻² s⁻¹ treatment, starch mobilization was already slower than in the control. In the 30 µmol m⁻² s⁻¹ treatment, degradation was still paced to dawn even though the dusk starch content was too low to cover essential maintenance costs, sugars fell to very low levels, C starvation reporter transcripts were strongly induced, and structural biomass was catabolized (Pilkington et al., 2015). This contrasts with the PRR7 transcript, which, compared to the control, showed no significant changes at 60 µmol m⁻² s⁻¹ and even showed a slight decrease during the night after a day at 30 µmol m⁻² s⁻¹. Therefore, it is unlikely that transcriptional regulation of PRR7 contributes to the slowing down of starch degradation after a low-light day. Although LHY and CCA showed a phase delay after a low-light day, this was negligible and nonsignificant in the 60 µmol m⁻² s⁻¹ treatment (Fig. 5). The only clock transcript to show a significant response at 60 µmol m⁻² s⁻¹ was ELF4, which decreased compared to control plants. Other clock transcripts showed no change in the 60 µmol m⁻² s⁻¹ treatment and only scattered changes in the 30 µmol m⁻² s⁻¹ treatment compared to the control. Incidentally, the very small effects of the 60 or 30 µmol m⁻² s⁻¹ treatments argue against the notion that clock dynamics respond to changes in metabolism that are likely to occur in natural light regimes.

Published data and our own experiments do not exclude the possibility that moderate changes in irradiance or C supply affect the abundance of clock proteins or the biological activities of these proteins. However, if there are such changes, they have little impact on the temporal dynamics of clock progression, except under severe C starvation. A role for putative changes in protein levels in the regulation of starch turnover would require that they impact starch turnover much more strongly than cognate targets within the core clock.

A Single Low-Light Day Triggers a Restriction of Growth and Increased Allocation to Starch in the Following Light Period Independently of Changes in the Transcriptional Clock

Many earlier studies found increased allocation to starch in growth conditions where the C supply is restricted (see “Introduction”). Subsequent studies in Arabidopsis (Gibon et al., 2004b, 2006; Mugford et al., 2014; Mengin et al., 2017) revealed that the primary event is a restriction of Suc consumption for growth in the light period and that the increase in allocation to starch is associated with a large increase of Glc and Fru. Hydrolysis of Suc to reducing sugars and their phosphorylation to hexose phosphates provides a mechanism to decrease net Suc synthesis and increase allocation to starch (Huber, 1989; Kingston-Smith et al., 1999; Macrae and Lunn, 2006; Stitt et al., 2010). This complex response is not explicitly addressed by the AD model, which focuses on starch degradation. In principle, it could be explained by RMS-type models because changes in clock dynamics in response to events in previous clock cycles might influence events in the coming cycle.

Our study shows that a single day of low irradiance leads to a decrease in the rate of growth, higher levels of reducing sugars, and an increase in allocation to starch when plants are returned to growth irradiance. This response might be viewed as a cautious growth strategy to deal with a fluctuating environment; low light in the previous 24-h cycle triggers a restriction of growth and an increase in reserve formation that reduces the risk of starvation in the coming night. Although growth was modeled in our study rather than measured directly, the estimated rates in the light and dark in this study correspond closely to those measured using ¹³CO₂ labeling of the cell wall and protein (Ishihara et al., 2015, 2017). Starch accumulation was not investigated in the light period following a day at low CO₂, but we assume accumulation would also have been stimulated, as metabolism and transcript abundance in the preceding 24-h cycle responded similarly in the low-CO₂ and 5 µmol m⁻² s⁻¹ irradiance treatments.

The restriction in growth, increase of reducing sugars, and increase in allocation to starch is unlikely to be explained by RMS-type models. The response was already significant in the 60 µmol m⁻² s⁻¹ treatment and did not become much larger in the 30 or 5 µmol m⁻² s⁻¹ treatments. In contrast, as already discussed, clock transcripts showed little or no change in the 60 µmol m⁻² s⁻¹ treatment and only scattered changes in the 30 µmol m⁻² s⁻¹ treatment. Possible reasons for the restriction of growth and increase in allocation to starch in the light period following a day with reduced irradiation will be discussed later.

Strong C Starvation Impacts the Circadian Clock at Multiple Sites

Although clock transcript dynamics were hardly affected by moderate reductions in irradiance, larger responses were seen in treatments that led to strong C starvation (Figure 11A). In very low light or low CO₂, the PRR7 transcript rose faster after dawn and declined more slowly and was present at slightly higher levels during the trough in the following night than in control plants. This is consistent with the proposal that low C induces PRR7 (Haydon et al., 2013). However, the response is negligible compared to the diel oscillation and only seen in treatments that lead to extreme C starvation.

Figure 11. — Schematic model for the impact of low C on the clock, clock outputs, and C allocation between growth and accumulation of starch. A, Schematic representation of the response of the clock to low C or low light. Blue denotes weaker action, and dark orange denotes stronger action. The clock is depicted schematically according to its progression through a 24-h cycle. The main responses of the clock components are indicated at the top of the diagram. For simplicity, interactions between the dawn and day components are not shown. Negative action of the dawn components on the dusk and evening components is proposed to be weakened due to attenuated negative action of EC function (due to repression of *ELF4* in low-C conditions) and the increased positive action by RVEs (which are induced in low C). Minor effects of low light, such as the disappearance of the secondary peak of GI transcript at ZT2-4, are not shown. Induction of *PIF*s (probably due to weakened negative action of EC) is assumed to have little functional impact in the treatment night because low sugars attenuate action of PIF-Pfr complexes (Shor et al., 2017). Inputs to *PRR7* and GI are indicated (pale blue), but these probably only occur under extreme C starvation. B, Schematic representation of the impact of the clock, output pathways involving *PIF* and *RVE* family members, and sugar levels on growth and starch accumulation in the recovery light period following a low-light day. The dotted line indicates slow reversal of the restriction of growth by low-C signaling.

Dalchau et al. (2011) proposed that Suc stabilizes the interaction of GI with ZTL in darkness, sequestering ZTL in the cytosol and preventing it from degrading TOC1 and PRR5 protein. GI was also recently reported to be a target of AKIN10/SnRK1.1 signaling (Shin et al., 2017). We observed little effect of low CO₂ on GI transcript, and this was largely restricted to the trough at the end of the night. Low light attenuated a minor secondary peak of GI transcript at ZT2, but this effect was nonsignificant except in extreme treatments. This minor peak has been reported previously (Locke et al., 2005; Edwards et al., 2010; Flis et al., 2016), but it is small compared to the major peak, and its functional significance is unclear. Our results indicate that the positive regulation of GI by light (Paltiel et al., 2006; Pokhilko et al., 2012) includes a high-fluence component.

The most responsive clock transcript in our study was ELF4. To our knowledge, ELF4 has not been implicated previously in C inputs to the clock. Low light and, to a lesser extent, low CO₂ led to a decrease in ELF4 transcript abundance at its peak at ZT10 and during the first part of the night compared to the control (Fig. 3, K and L). The response at night was significant after a moderate reduction in irradiance. Repression of ELF4 might weaken EC repressor function at ZT14∼16 when the EC targets several day and dusk clock components (Kolmos et al., 2009; Dixon et al., 2011; Helfer et al., 2011; Pokhilko et al., 2012, 2013) and clock outputs like PIFs (Nusinow et al., 2011). In agreement with this, low-light and low-CO₂ treatments attenuated the decay of EC targets like PRR5, TOC1, and PIF transcripts.

Transcript abundance for PRR5, TOC1, and LUX was higher in the very-low-light and low-CO₂ treatments than in the control. These transcripts usually decline rapidly after their peak at ZT8 to 10 before rising to a minor peak at ZT16 to 20 (Fig. 3, E, F, I, and J; Supplemental Fig. S8, E and F; Strayer, 2000; Hsu et al., 2013; Flis et al., 2016). A possible explanation for the minor peak is that there is a strong repressing signal from ZT8 to 10 onwards, presumably from the EC and/or PRRs, which later weakens to allow the partial recovery of dusk and evening transcripts at ZT16 to 20, after which repression by CCA1 and LHY proteins begins. In the low-irradiance or low-CO₂ treatments, PRR5, TOC1, and LUX declined more slowly, resulting in a broad plateau over much of the night. Increased nighttime levels of transcripts for dusk genes might in turn delay derepression of LHY and CCA1 at ZT20∼24, leading to the small phase delay at the following dawn in the lowest light treatment (Fig. 5A).

The higher nighttime levels of PRR5 and TOC1 transcripts might be due to a combination of internal loops and external inputs. One contributor might be abrogated EC repressor function at ZT14∼16. A second might be the attenuated minor peak in GI transcript at ZT2 to 4; GI is known to act via ZTL to repress TOC1 and evening components (Más et al., 2003; Kim et al., 2007; Pokhilko et al., 2012). A third may be weakened repressor function of LHY and CCA1. Although these two transcripts fell more slowly between ZT2 and ZT6 in the lowest irradiance, the targets of repression by LHY and CCA1, PRR5 and TOC1, were expressed at the same time or slightly earlier than in the control. The weakened repressor function may be due to increased RVE expression.

Low Light and Low C Impact Clock Inputs and Outputs Mediated by PIFs and RVEs

Many PIFs and RVEs operate as clock outputs (Martínez-García et al., 2000; Zhang et al., 2007; Oh et al., 2009; Rawat et al., 2009; Nusinow et al., 2011), and there is mounting evidence that some operate as clock inputs (Rawat et al., 2011; Hsu et al., 2013; Shor et al., 2017). Low light or C had a larger impact on the diel dynamics of many PIF and RVE transcripts than on clock transcripts (Figs. 7–9), indicating that PIFs and RVEs may provide a conduit for light or C inputs to circadian signaling (Fig. 11A). PIF transcripts decline during the night due to repression by EC (Nusinow et al., 2011). Low light and, to a lesser extent, low CO₂ attenuated this decline for several PIFs, possibly reflecting abrogation of EC repressor function. Partial stabilization of PIF4 transcript was significant after a moderate reduction in irradiance (Fig. 7). PIFs mediate the induction of many genes, including circadian components in a Suc-dependent manner (Shor et al., 2017), with the response to Suc itself depending on light quality and temperature (Shor et al., 2018).

Low light and low CO₂ led to increased abundance of many RVE transcripts. For example, the decline of RVE4 transcript was attenuated in very low light or low CO₂. As already noted, a 2- to 3-fold increase in RVE4 transcript abundance at its trough between ZT4 and ZT16 in low light or low CO₂ represents a substantial increase in total RVE4 plus RVE6 plus REV8 transcript at this time. RVE4, RVE6, and RVE8 are positive effectors of many clock genes (Farinas and Mas, 2011; Rawat et al., 2011; Hsu et al., 2013; Shalit-Kaneh et al., 2018). Higher levels of RVEs represent one of the most marked responses of the clock to low C and may counteract the repressor function of LHY and CCA1, as well as contribute to the slower decay of dusk and evening components and the rise of PRR9 transcript in the night after a low-light day.

Multiple Factors Contribute to the Restriction of Growth and Increased Allocation to Starch following a 24-h Cycle with Low C

C signaling is probably largely responsible for the restriction of growth at night following a low-irradiance light period. It may also contribute to the restriction of growth and increase in allocation to starch in the light period following a low-irradiance 24-h cycle (Fig. 11B). Falling C inhibits TOR, bZIP, and Tre6P signaling and activates SnRK1 signaling (Hanson and Smeekens, 2009; Robaglia et al., 2012; Lunn et al., 2014; Dobrenel et al., 2016), represses cohorts of genes required for growth (Contento et al., 2004; Price et al., 2004; Usadel et al., 2008; Cookson et al., 2016), and inhibits protein and cell wall synthesis (Pal et al., 2013; Ivakov et al., 2017). Crucially, these responses are triggered by moderate changes in C, before the plant becomes acutely starved (Smith and Stitt, 2007; Usadel et al., 2008; Pal et al., 2013; Cookson et al., 2016). In our experiments, a moderate decrease in irradiance activated low-C signaling, as indicated by the responses of C reporter transcripts (Fig. 2; Supplemental Figs. S6 and S7). Intriguingly, modeling indicated that growth was restricted in the following light period even though sugars were at higher levels than in control plants. This implies either that there is a delay until low-C signaling is reversed or that additional factors are restricting growth. These possibilities are not mutually exclusive.

In addition to direct effects on metabolism and growth, C signaling may modulate clock outputs that themselves regulate metabolism and growth (Fig. 11B). Low-light treatments led to larger changes in the phase and peak abundance of the GBSS2 transcript at the following dawn than those of the dawn clock genes (Figs. 3A, 5, and 6). They also had a larger impact on many PIF and RVE transcripts than on core clock transcripts (see "Low Light and Low C Impact Clock Inputs and Outputs Mediated by PIFs and RVEs"). There is already evidence that RVEs can restrict growth. Rawat et al. (2009) found that RVE1 inhibits hypocotyl elongation by increasing auxin and proposed that this represents a response to low-C availability. Gray et al. (2017) recently reported that RVE4, RVE6, and RVE8 inhibit Suc-promoted growth in seedlings and that RVE3 and RVE5 strengthen this inhibition. Our analyses reveal that low light or low C induce RVE1, RVE2, RVE3, RVE4, RVE7, and RVE8, with the responses of RVE1, RVE2, and RVE3 being significant in the 60 µmol m⁻² s⁻1 treatment. This is consistent with a scenario in which low C in the preceding 24-h cycle promotes expression of RVEs, which act to restrict the use of sugars for growth in the following light period.

MATERIALS AND METHODS

Plant Growth

Arabidopsis (Arabidopsis thaliana) Col-0 seeds were spread on wet soil (Stender AG Schermbeck) in 10-cm-diameter plastic pots in 30 × 50 × 6-cm trays, left overnight at 4°C in the dark under lids, transferred to a 12-h photoperiod (160 µmol m⁻² s⁻¹, 21°C in light and 19°C in dark; Percival E-36 L chamber, CLF Plant Climatics), and thinned to 9 plants/pot after a week. The harvest day protocol is described in Supplemental Figure S1. Irradiance was decreased by dimming or filters. The low CO₂ treatment was carried out in Plexiglas chambers (Ishihara et al., 2015). At each sampling point, three replicates (each 4–6 rosettes) were collected from different parts of the chamber into liquid nitrogen.

Respiration and Photosynthesis

Gas exchange was measured using a LI-6400XT Portable Photosynthesis System fitted with the 6400-17 Whole Plant Arabidopsis Chamber (LI-COR Biosciences, d-61352; Mengin et al., 2017).

Transcripts

RNA was extracted and transcripts analyzed by reverse transcription quantitative PCR including defined amounts of six artificial RNAs as internal standards to allow calculation of copy number as described by Flis et al. (2015) except for normalization between technical replicates. Timing of peak abundance was calculated based on average peak timing of bootstrapped time series using both polynomial fit and spline smooth (B = 15 for each method). Fits were optimized for minimum second-order Akaike’s information criterion.

Metabolites

Starch and metabolites were assayed (two technical replicates per biological replicate) as described previously (Gibon et al., 2002, 2004a; Cross et al., 2006; Nunes-Nesi et al., 2007).

Calculation of Growth Rate

C allocation to structural biomass was estimated using a whole-plant C balance model (Sulpice et al., 2014). The amount of C in starch, Suc, Glc, Fru, malate, fumarate, and amino acids was calculated as the amount of a given metabolite (nmol g⁻¹FW) multiplied by the number of C atoms in the molecule (12 for Suc; six for starch, Glc, and Fru; and four for malate, fumarate, and amino acids) and summed across all metabolites at a given time point. The rate of C deposition in metabolites (∆C) was calculated as the difference in total summed C between two time points divided by the time interval between the time points. C allocation to growth was estimated in the light period as A_day − ΔC_day and growth at night as ΔC_night − R_night, where A_day and R_night are the net rate of C assimilation in the light and the net rate of respiratory C loss during the night, respectively. ses were estimated using Gaussian error propagation (Birge, 1939; Ku, 1966).

Calculation of Rates of Starch Accumulation and Mobilization and Expected Time of Starch Exhaustion

Rates of starch accumulation and mobilization were estimated using linear models describing starch levels as a function of time (starch = a.ZT + b). Linear fits were applied to data for the light and dark periods (biological replicates were not averaged). Rate was calculated from the slope (a) of the fit linear models and the 95% confidence interval from the Student’s t distribution (se times the area covering 95% of a normal distribution). The expected time of starch exhaustion was estimated from the root of the linear fitting (= the ZT value when starch amount equals 0; f(ZT) = 0) using a nonderivative approach (Anderson, 1974; R Core Team, 2017).

Statistical Procedures

Technical replicates were always averaged prior to statistical analysis, and biological replicates were kept separate. Significance of changes in metabolite and transcript levels was tested using ANOVA or t tests, comparing each treatment with the control at each time point, and on all time points in a defined time interval (see Supplemental Text S1). Other statistical analyses are also described in Supplemental Text S1.

Accession Numbers

These are provided in Supplemental Table S4.

Supplemental Data

The following supplemental materials are available.

Supplemental Figure S1. Experimental design and sampling scheme (supplemental information to Figs. 1–9).
Supplemental Figure S2. Photosynthesis and respiration (supplemental information to Fig. 1).
Supplemental Figure S3. Further metabolites: temporal dynamics (supplemental information to Fig. 1)
Supplemental Figure S4. Starch and metabolites; statistical analyses (analyses of data shown in Fig. 1 and Supplemental Fig. S3, which underlie the compilation in Fig. 2A).
Supplemental Figure S5. Starch and metabolites; principal component analysis (analyses of the data shown in Figure 1 and Supplemental Fig. S3, that underlie the display in Fig. 2G).
Supplemental Figure S6. Carbon reporter genes; temporal dynamics of transcript abundance (supporting data for Fig. 2B).
Supplemental Figure S7. Carbon reporter genes; statistical analyses (supporting analyses for Fig. 2B; calculations were essentially as in Supplemental Fig. S4).
Supplemental Figure S8. Clock gene transcript abundance; temporal dynamics (supplemental information to Fig. 3).
Supplemental Figure S9. Clock and GBSS1 transcript abundance; statistical analysis (supplemental information to Figs. 3, 4 and 6). The display and calculations are described in the legend to Supplemental Figure S7.
Supplemental Figure S10. PIF family member transcript abundance; temporal dynamics (supplemental data and analyses to Fig. 7).
Supplemental Figure S11. PIF family member transcript abundance; statistical analysis and compilation of response profiles (supplemental analyses to Fig. 7 and Supplemental Fig. S10).
Supplemental Figure S12. RVE family member transcript abundance; temporal dynamics (supplemental data and data analysis to Fig. 8).
Supplemental Figure S13. RVE family member transcript abundance; statistical analysis and compilation of response profiles (supplemental analyses to Fig. 8 and Supplemental Fig. S12).
Supplemental Figure S14. Meta-analysis of a published data set for responses of clock genes transcript abundance to carbon (underlying analyses to Fig. 10).
Supplemental Figure S15. Meta-analysis of a published data set for responses of PIF family member transcript abundance to carbon (underlying analyses to Fig. 10).
Supplemental Figure S16. Meta-analysis of a published data set for responses of RVE family member transcript abundance to carbon (underlying analyses to Fig. 10).
Supplemental Table S1. Starch and metabolites and estimation of the rate of C deposition in biomass.
Supplemental Table S2. Transcript abundance and estimates of peak timing and its 95% confidence interval.
Supplemental Table S3. Response of clock, PIF, and RVE transcript abundance to treatments that alter C availability (underlying data for Supplemental Figs. S15–S17).
Supplemental Table S4. Accession numbers.
Supplemental Text S1. Statistical methods.
Supplemental Text S2. Analysis of the response of clock genes and PIF and RVE family members to changes in light and C in a compilation of light and C treatments (background to Fig. 10 and Supplemental Figs. S14–S16)

Acknowledgments

T.A.M is especially grateful to Dr. Armin Schlereth for support in sample processing. We thank Andrew Millar and Alison M. Smith for discussion.

Footnotes

This article was supported by the Max Planck Society, the European Union (FP7 TiMet, contract 245143), and the Brazilian National Council for Scientific and Technological Development (CNPq, contract 246681/2012-8).

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PERMALINK

Response of the Circadian Clock and Diel Starch Turnover to One Day of Low Light or Low CO21,[OPEN]

Thiago Alexandre Moraes

Virginie Mengin

Maria Grazia Annunziata

Beatrice Encke

Nicole Krohn

Melanie Höhne

Mark Stitt

Abstract

RESULTS

Gas Exchange, Starch, and Metabolites

Figure 1.

Figure 2.

C Status Estimated by Integrated Analysis of Metabolite Levels

C Status Estimated by the Abundance of C-Responsive Transcripts

Estimation of Growth Rates Using a Whole-Plant C Model

Clock Transcripts

Figure 3.

Figure 4.

Figure 5.