Supplemental Text S1 Explanation for supplemental Figures S6-S9.

Genes encoding cytosolic, plastidic and mitochondrial ribosomal proteins were identified using the MapMan ontology. Data for responses of their transcript levels was viewed via a web link (http://mapman.mpimp-golm.mpg.de/supplement/xn/figures.shtml) presented in Usadel et al. (2008). Screen shots are provided in the supplemental material (Supplemental Fig. S6). This display contains three components; (i) a documentation of the response of the transcript levels to three inputs that regulate diurnal gene expression (light, C, the clock), (ii) a documentation of the diurnal changes of the transcripts and (iii) the results of a model that attempts to predict these diurnal changes from the responses of the transcripts to light, C and the clock.

In more detail, Supplemental Fig. S6 shows (summarizes (from left to right) for each gene, (i) the measured response to two treatments that characterize the response to light (short exposure of etiolated Col-0 seedlings to light; response of Arabidopsis rosettes to 4 h light at sub-compensation point CO2 at the end of the night compared to a 4 h extension of the nights (Bläsing et al., 2005), (ii) the measured response to two treatments that increase C levels (response of Col-0 seedlings to 3 h exogenous supply of sucrose, Osuna et al., 2007; response of Col-0 rosettes to 4 h illumination with ambient 350 ppm CO2 compared to 4 h illumination at 50 ppm sub-compensation point CO2, Bläsing et al., 2005) and (iii) the response during a free-running circadian cycle (Edwards et al., 2006). These are termed ‘inputs’ The treatments in rosettes are used in the model (see below); the light and C treatments in seedlings are provided as a check for the generality of the response..

The display also shows for each gene (iv) the measured response in a diurnal cycle and (v) an extended night in Col-0, and (vi) the measured response in a diurnal cycle in pgm. These are termed ‘outputs’. There are in total 17 output data sets (6 in the diurnal cycle and 5 in the extended night in Col-0, and 6 in the diurnal cycle in pgm; dawn/dusk time points are shared).

A simple linear model using light, C and the circadian clock as inputs was used to predict the response of each gene (vii) in Col-0 during a diurnal cycle and (viii) an extended night and (ix) in pgm in a diurnal cycle.

Briefly, the response of each gene to light is defined by the response in rosettes to 4 h light at

50 ppm CO2 compared to a 4 h extension of the night, the response of each gene to C is defined by the response to illumination of rosettes at 350 ppm as compared to 50 ppm CO2, , and the free-running circadian dataset is used define the response of each gene to the circadian clock. The model attempts to predict the response of all 22K genes on the Affymetrix array from a linear combination of the response to light pus the response to C plus the response to the clock at a given time in the circadian cycle. Each input is multiplied by a separate weighting factor, which is the same for all genes for this input. The weightings are independently varied to optimize the fit for a given output data set. This procedure is repeated for each of the 17 output data sets ( i.e. each time point in the diurnal cycle and extended night treatment in Col-0, and each time point in the pgm diurnal cycle), resulting in 17 models with different weightings and fits (for details see Usadel et al., 2008). The fit (the R2 of the plot of the measured responses vs. the predicted response for all 22K genes) of the model was much stronger than for any individual input, It was >0.3 for most models, and often >0.4, with especially good fits (>0.5) in Col-0 in an extended night and in pgm in the night (see Usadel et al., Table IV). The weighting was usually highest for C, identifying C- signaling as the single most important input determining global transcription profiles in these conditions. Light always had a positive weighting in the light, and a negative weighting in the dark (Usadel et al., 2009; Table IV, Figure 11B), whilst the weighing of C was strongly correlated with the sucrose content (Usadel et al., 2009 Figure 11A-B). Further, the weighing of C was higher in pgm than in Col-0, with more strong positive values in the light and stronger negative values in the night (Usadel et al., 2009, Table IV and Figure 11B)..

A more detailed analysis of the response to the C supply and during the diurnal cycle is provided in Supplemental Figs. S7 for transcripts that encode cytosolic ribosomal proteins, and in Supplemental Fig. S8 for transcripts that encode plastidic ribosomal proteins.

Cytosolic ribosomal proteins Supplemental Figs. S6A documents that transcripts for almost all of the major cytosolic ribosomal proteins are induced by sugars.. Transcripts for cytosolic ribosomal proteins increase after addition of sugars to C-starved seedlings (Price et al., 2004; Osuna et al., 2007),. They increase slightly in the light and decrease in the dark in a diurnal cycle in Col0, and show an accentuated rhythm in pgm (Bläsing et al., 2005). The increase in the light is suppressed when rosettes are illuminated at compensation point [CO2] (Bläsing et al., 2005).

Almost all of the transcripts for ribosomal proteins show very similar responses to sugar addition, to changes in CO2 and during diurnal cycles (Supplemental Fig. S7A-C). The linear model of Usadel et al. (2008) predicted the diurnal changes of most of these transcripts very well (Supplemental Figs. S6A; S7D). with sucrose being the main input. However, the diurnal changes in transcripts do not generate significant diurnal changes in ribosome abundance, even in pgm (see Fig. 8). The similar absolute levels of ribosomes in Col-0 and pgm (Fig. 8) may be explained because the average level of transcripts for ribosomal proteins though the diurnal cycle is similar in both genotypes.

The response of plastid ribosomal protein transcript was more complex. They showed a much more diverse response to sucrose, with some being induced and many others being repressed (Supplemental Figs. S6B; S8). Correspondingly, some were induced but many others were repressed in the light period in Col0. This disparate response is especially clear in treatments that led to a large increase of sugars, like sucrose addition to starved seedlings (Supplemental Fig. S8A) or a comparison of pgm with Col0 in the light (Supplemental Fig. S8B-C). Further, transcripts for plastidic ribosomal proteins often showed circadian regulation (Supplemental

Fig. S6B). Their responses to sugar addition or changes in CO2 concentration were very different to those seen between dawn and dusk (Supplemental Fig. S8A-C) and their diurnal changes were often poorly predicted by the linear model (Supplemental Fig. S6B). Further, the levels of many, though not all, of the transcripts were lower in pgm than in wild-type Col0 (Supplemental Fig. S6B; 8B-C). Thus, the decrease in plastidic rRNA in pgm (see Fig. 8) is accompanied by a lower level of transcripts for many plastidic ribosomal proteins.

Transcripts for mitochondrial ribosomal proteins showed a similar pattern to the cytosolic ribosomal proteins (Supplemental Fig. S6C). Many were sugar-induced, showed small diurnal changes in wild-type Col0 that were amplified in pgm, the increase in the light was suppressed in low CO2, and the responses were well-predicted by the linear model.

Supplemental Fig. 9 shows the responses of selected genes that are required for the assembly of cytosolic ribosomes. These are all rather unresponsive to light, strongly induced by sucrose, show only weak circadian responses, are induced in the light and decrease in the night in Col0, decrease strongly in an extended night, and in pgm show much more exaggerated diurnal changes than in Col0. These responses highlight the cytosolic ribosome assembly genes as strongly sugar-regulated, with highly coordinated responses to those of cytosolic ribosomal proteins. The reader can further explore these responses, and that of other genes of interest, at the web site http://mapman.mpimp-golm.mpg.de/supplement/xn/figures.shtml. Genes should be entered using their Affymetrix identifier.

List of ribosomal protein genes used in this analysis

246068_at at5g20290 265805_s_at at4g36130 258569_at at3g04400 251409_at at3g60245 261490_at at1g14320 253291_at at4g33865 250159_at at5g15200 258712_s_at at3g09680 261789_at at1g15930 263821_s_at at5g18380 259612_at at1g52300 264421_at at1g43170 252235_at at3g49910 262985_s_at at1g70600 257753_at at3g18740 259006_at at3g09200 261416_at at1g07770 245841_s_at at1g58380 260426_at at1g72370 258715_at at3g09630 245342_at at4g16720 265963_s_at at3g11940 258709_at at3g09500 254655_s_at at5g46430 252294_at at3g49010 253901_at at4g27090 259239_at at3g11510 246503_at at5g16130 255706_at at4g00100 249310_at at5g41520 250973_at at5g02870 260497_at at2g41840 251185_at at3g62870 252693_s_at at3g44010 257599_at at3g24830 261362_s_at at3g55750 265736_at at2g01250 261620_s_at at1g33140 253248_at at4g34670 246747_at at5g27700 261578_at at1g01100 262117_at at1g02780 260369_at at1g69620 258858_at at3g02080 250862_s_at at2g04390 246758_at at5g27850 258900_at at3g05590 257906_at at3g25520 264233_at at1g67430 262163_at at1g77940 248331_at at5g52650 259096_at at3g04840 266699_at at2g19730 252601_s_at at3g45030 267007_at at2g34480 251997_at at3g53020 254617_s_at at5g45775 259112_at at3g05560 245355_at at4g17390 247566_at at5g61170 255789_at at2g33370 251357_at at3g61110 258837_at at3g07110 258486_at at3g02560 263667_at at1g04270 254012_at at4g26230 251938_at at3g53430 247654_at at5g59850 248747_at at5g47930 264679_s_at at1g09690 263286_at at2g36160 250440_at at5g10360 258296_at at3g23390 245121_at at2g47610 266258_at at2g27720 260383_s_at at1g74060 250895_at at5g03850 251341_at at3g60770 251926_at at3g53740 249795_at at5g23740 247968_at at5g56670 252297_at at3g48930 247584_at at5g60670 266256_at at2g27710 246745_at at5g27770 253487_at at4g31700 263665_at at1g04480 260538_at at2g43460 252566_at at3g46040 263400_s_at at3g53870 245311_at at4g14320 249700_at at5g35530 255000_at at4g09800 249466_at at5g39740 266981_at at2g39460 266210_at at2g27530 265445_at at2g37190 256385_at at1g66580 256438_s_at at2g40205 251737_at at3g56340 247978_at at5g56710 264203_at at1g22780 251486_at at3g59540 256143_at at1g48830 251018_at at5g02450 246730_at at5g28060 246379_s_at at1g57660 258284_at at3g16080 251921_at at3g53890 245372_at at4g15000 263691_at at1g26880 265210_at at2g36620 255776_at at1g18540 265671_at at2g32060 263585_at at2g25210 263289_at at2g36170 252912_at at4g39200 264438_at at1g27400 253715_at at4g29390 264849_at at2g17360 256794_at at3g22230 258090_at at3g14600 255657_at at4g00810 254049_at at4g25740 250667_at at5g07090 248768_at at5g47700 253482_at at4g31985 249815_at at5g23900 267213_at at2g44120 252055_at at3g52580 247010_at at5g67510 255520_at at4g02230 255977_at at1g34030 259090_at at3g04920 247815_at at5g58420 245639_at at1g25260 257141_at at3g28900 247900_at at5g57290 253728_at at4g29410 254763_at at4g13170 251783_at at3g55280 260258_at at1g74270 246070_at at5g20160 252413_at at3g47370 266705_at at2g19750 247267_at at5g64140 254831_at at4g12600 252643_at at3g44590 258532_at at3g06700 266700_at at2g19740 263372_at at2g20450 251552_at at3g58700 251007_at at5g02610 263519_at at2g21580 258521_at at3g06680 250703_at at5g06360 258922_at at3g10610 260026_at at1g29970 254980_at at4g10450 245886_at at5g09510 255819_s_at at2g40590 258410_at at3g16780 256648_at at3g13580 258937_at at3g10090 267174_at at2g37600 254030_at at4g25890 266980_at at2g39390 248800_at at5g47320 261911_at at1g80750 267507_at at2g45710 248655_at at5g48760 263973_at at2g42740 266822_at at2g44860 265338_at at2g18400 263686_at at1g26910 258995_at at3g01790 256065_at at1g07070 251834_at at3g55170 259130_at at3g02190 258799_at at3g04770 251638_at at3g57490 253202_at at4g34555 254355_at at4g22380 256253_at at3g11250 246538_at at5g15520 253598_at at4g30800 261888_at at1g80800 262594_at at1g15250 251538_at at3g58660 259271_at at3g01170 265032_at at1g61580 249424_s_at at5g40080 256597_at at3g28500 266684_at at2g19720 265730_at at2g32220 258576_at at3g04230 259392_at at1g06380 249427_at at5g39850 267349_at at2g40008 253726_at at4g29430 257663_at at3g20260 252144_at at3g51190 256388_at at3g06180 263602_at at2g16360 263016_at at1g23410 256460_at at1g36240 247739_at at5g59240 256654_at at3g18880 245170_at at2g47570 261200_at at1g12960 249381_at at5g40040 249423_at at5g39785 249738_at at5g24510 255535_at at4g01790 245890_at at5g09490 252283_at at3g48960 262132_at at1g02830 245782_at at1g35200 255950_at at1g22110 260382_at at1g73850 259316_at at3g01175 247416_at at5g63070 245883_at at5g09500 249390_at at5g40130 252259_at at3g49460 252347_at at3g48130 251604_at at3g57820 249418_at at5g39785 266972_at at2g39590 249105_at at5g43640 245471_at at4g16030 254856_at at4g12160 256434_at at3g10950 256572_at at3g30740 List of plastid ribosomal protein genes used in this analysis

257223_at atcg00160 244969_at atcg01120 255623_at atcg00380 244968_at at1g70190 244982_at atcg00800 264575_at at5g51610 261078_at atcg01230 247201_at atcg00810 244988_s_a t atcg00790 263131_at at1g29070 244939_at atcg00660 258404_at atcg01310 244981_at at3g27840 262172_at atcg00650 267435_at at4g01310 244986_at atcg00640 250190_at atcg00780 244980_at at1g05190 244979_at at1g07320 261954_at at5g65220 253138_at atcg00840 261119_at at1g78630 251120_at atcg00065 267088_at at3g17465 245005_at atcg00770 258076_at at1g74970 251883_at at2g33800 248174_at atcg00820 245357_at at5g14320 262235_at atcg00760 248798_at atcg00750 261190_at at1g64510 257190_at at4g35490 245049_at at1g75350 249331_at at3g63490 255850_at at2g38140 249742_at atcg00330 262029_at at3g25920 265247_at at3g54210 260165_at at5g54600 250058_at at4g17560 256855_at at1g48350 246339_at at5g47190 246517_at at1g32990 262283_at at3g13120 245852_at atcg00050 253549_at at5g40950 258466_at at2g33450 259678_at at5g24490 246210_at at1g35680 244992_s_a t at2g43030 253773_s_a t at1g79850 257225_s_a t at5g17870 266535_s_a t at3g15190 244960_at at3g44890 246294_at at5g15760 at1g68590 at5g13510 at4g30930 at3g06040 at1g77750 at4g36420 atcg00900 at4g28360 at3g27850 at2g16930 atcg01020 at3g56910