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The Chlamydomonas reinhardtii Organellar Genomes Respond Transcriptionally and Post-Transcriptionally to Abiotic Stimuli

Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York 14853

¹ To whom correspondence should be addressed. E-mail ds28{at}cornell.edu; fax 607-255-6695

	Abstract

TOP Abstract INTRODUCTION RESULTS DISCUSSION METHODS References

 
The Chlamydomonas reinhardtii plastid and mitochondrial transcriptomes were surveyed for changes in RNA profiles resulting from growth in 12 culture conditions representing 8 abiotic stimuli. Organellar RNA abundance exhibited marked changes during nutrient stress and exposure to UV light, as revealed by both RNA gel blot and DNA microarray analyses. Of particular note were large increases in tufA and clpP transcript abundance during nutrient limitation. Phosphate and sulfur limitation resulted in the most global, yet opposite, effects on organellar RNA abundance, changes that were dissected further using run-on transcription assays. Removal of sulfate from the culture medium, which is known to reduce photosynthesis, resulted in 2-fold to 10-fold decreases in transcription rates, which were reflected in lower RNA abundance. The decrease in transcriptional activity was completely reversible and recovered to twice the control level after sulfate replenishment. Conversely, phosphate limitation resulted in a twofold to threefold increase in RNA abundance that was found to be a post-transcriptional effect, because it could be accounted for by increased RNA stability. This finding is consistent with the known metabolic slowdown under phosphate stress. Additionally, inhibitor studies suggested that unlike those in higher plants, Chlamydomonas chloroplasts lack a nucleus-encoded plastid RNA polymerase. The apparently single type of polymerase could contribute to the rapid and genome-wide transcriptional responses observed within the chloroplast.

	INTRODUCTION

TOP Abstract INTRODUCTION RESULTS DISCUSSION METHODS References

 
Plant cells partition photosynthesis and respiration into two semiautonomous compartments: chloroplasts and mitochondria. These organelles contain up to several thousand proteins, of which 95% are nucleus encoded; however, the remaining organelle-encoded proteins generally are essential for energetic functions and, in some cases, for viability (Bowsher and Tobin, 2001). In addition to photosynthesis, chloroplasts store carbohydrates and are the site of synthesis for key metabolites, such as heme precursors, amino acids, purines, pyrimidines, and fatty acids (Buchanan et al., 2000). Plant mitochondrial functions are conserved (ATP production and organic and amino acid synthesis), but the mitochondrial genomes of photosynthetic species are highly variable in size, sequence, and composition (Gray, 1999; Knoop and Brennicke, 2002). The regulation of photosynthesis and respiration requires myriad factors to coordinate the coexpression of nucleus- and organelle-encoded partners in response to environmental cues, developmental signals, and other processes (Gruissem and Tonkyn, 1993; Surpin and Chory, 1997; Leon et al., 1998; Yu et al., 2001). Although nuclear gene regulation often is transcriptional, organellar gene regulation has been documented at both the transcriptional (Mulligan et al., 1991; Rapp et al., 1992; Mullet, 1993; Kristal et al., 1994; Binder et al., 1996) and post-transcriptional (Finnegan and Brown, 1990; Rochaix, 1992; Gillham et al., 1994; Drager and Stern, 1998; Menassa et al., 1999; Giege et al., 2000) levels. However, these individual studies remain to be integrated into a global analysis of organellar responses to abiotic stimuli.

In vascular plants, in which chloroplast maturation is a highly visible developmental process, plastid gene regulation has been examined thoroughly (Mayfield et al., 1995; Barkan, 1998). During the transition from proplastid to mature chloroplast, plastid-encoded genes are transcribed by two temporally regulated RNA polymerases (RNAPs) (Allison, 2000). One RNAP is encoded by the nuclear genomes of many streptophytes and is related to those of phages such as T7; it has been termed NEP for nucleus-encoded polymerase. NEP is highly expressed in nonphotosynthetic plastids and is responsible for transcribing the genes that specify the Escherichia coli–like plastid-encoded RNA polymerase (PEP), whose transcriptional targets are primarily the photosynthetic genes (Hajdukiewicz et al., 1997). Early in development, NEP activity predominates, but PEP activity eventually overtakes it (Baumgartner et al., 1993; Dubell and Mullet, 1995). Within the plastid, the primary determinant of polymerase utilization is promoter type, of which at least two are recognized by NEP and one by PEP (Hajdukiewicz et al., 1997; Liere and Maliga, 1999). However, data from tobacco plants engineered to lack PEP suggest that NEP specificity may be diminished in the absence of PEP, although PEP is essential for photosynthesis (Legen et al., 2002). In the unicellular green alga Chlamydomonas reinhardtii, which possesses only chloroplasts, promoters cannot be organized into wholly distinct classes (Klein et al., 1992), and attempts to disrupt genes encoding PEP have been unsuccessful (Goldschmidt-Clermont, 1991; Fischer et al., 1996). This fact suggested that, unlike higher plants, Chlamydomonas might require PEP even when growing heterotrophically.

Although the extent of transcriptional regulation in plastids is still somewhat enigmatic, post-transcriptional regulation is well known (Goldschmidt-Clermont, 1998). These processes can be divided into three classes: cleavage/splicing of primary transcripts, control of mRNA stability, and translational regulation. In angiosperms, the importance of these mechanisms can be illustrated by the psbB gene cluster, which has a single promoter yet encodes numerous RNAs that specify components of two major photosynthetic complexes (photosystem [PS] II and cytochrome b₆/f), whose ratio is dependent on light intensity (Herrmann et al., 1985) and cell type (Schuster et al., 1986). Both maize (Barkan et al., 1994) and Arabidopsis (Felder et al., 2001) nuclear mutants have been isolated that cause photosynthesis defects as a result of blocks in post-transcriptional steps of psbB gene cluster expression.

In Chlamydomonas, nuclear mutants that affect the accumulation but not the transcription of specific plastid RNAs have been isolated (Rochaix, 1996). These mutants typically are defective in proteins that protect the 5' end from degradation but that also may function in RNA processing and translation (Drager et al., 1998; Boudreau et al., 2000; Vaistij et al., 2000). Together with these stability factors, enzymes act to degrade the processed transcripts—for example, through a polyadenylation-mediated pathway (Schuster et al., 1999; Komine et al., 2002)—thus modulating the translatable RNA pool within the plastid.

The transcriptional and post-transcriptional processes described above can be modulated by environmental stimuli (Goldschmidt-Clermont, 1998), most notably light quantity and quality and temperature extremes (Mayfield et al., 1995). Light, beyond inducing the proplastid/etioplast-to-chloroplast conversion, has been shown to alter transcription rates and increase the degradation of specific photosynthetic gene transcripts (Glick et al., 1986; Deng et al., 1989). In addition, chloroplast mRNA levels in Chlamydomonas were shown to fluctuate with diurnal change, mediated through transcription and RNA degradation (Leu et al., 1990); in another study, a sampling of seven chloroplastic RNAs showed that they were subject to higher degradation rates in the light (Salvador et al., 1993). It has been reported that heat stress in maize correlates with increases in transcription rates for five plastid genes and reduces the levels of cytosine-to-uridine editing (Nakajima and Mulligan, 2001). Linked to environmental stimuli are changes in reducing potential and ATP concentration, broadly categorized as the redox state (Levings and Siedow, 1995; Surpin et al., 2002). It has been reported that by inducing changes in electron transport (e.g., in photosynthetic mutants or by the addition of electron transport chain inhibitors), alterations in plastid transcription and RNA degradation rates occur (Allen, 1993; Pfannschmidt et al., 1999; Salvador and Klein, 1999). Redox state also has been reported to regulate plastid translation (Trebitsh et al., 2000). There is limited information, however, regarding whether and how other environmental factors contribute to redox changes or affect plastid gene expression in other ways.

Although Chlamydomonas has been a model organism for the dissection of photosynthetic processes (Dent et al., 2001; Raven and Girard-Bascou, 2001), the lack of a complete chloroplast genome sequence and the associated genomic tools have been obstacles to global investigations into chloroplast gene regulation. The Chlamydomonas genome project (http://www.biology.duke.edu/chlamy_genome/) recently resulted in a complete chloroplast genome sequence (Maul et al., 2002), and two arrays have been developed (see the genome World Wide Web site and below). In this study, we used the complete chloroplast and mitochondrial genome sequences to analyze organellar RNA abundance and transcription rates under 11 nonoptimum culture conditions. The results show sometimes surprisingly strong responses to abiotic stimuli, which occur at both the transcriptional and post-transcriptional levels.

	RESULTS

TOP Abstract INTRODUCTION RESULTS DISCUSSION METHODS References

 
Chloroplast Transcript Accumulation Changes with Culture Conditions
With the full Chlamydomonas chloroplast genome sequence newly available, we sought to examine how the plastid transcriptome responds to various environmental stimuli while simultaneously searching for newly expressed regions. Such new genes might correspond to some of the many apparently unique open reading frames whose expression had not been examined previously. A whole-genome "northern walk" was chosen as the approach most likely to reveal small or low-abundance RNAs. Because repetitive DNA represents 20% of the entire sequence and is endemic within the intergenic regions (Maul et al., 2002), we used 45 gene-specific probes and 6 intergenic fragments amplified by PCR rather than simply using overlapping clones. These same probes served as the foundation of an organelle-based DNA microarray. Because some chloroplast genes have been shown to be expressed differentially (e.g., in light versus dark [Salvador et al., 1993]), 11 culture conditions were explored in RNA gel blot analyses. These included five variations in light intensity, quality, and duration, four media lacking specific nutrients, and two altered temperatures (12 and 37°C). Each of these conditions was compared with the standard laboratory Chlamydomonas culture medium (Tris-acetate-phosphate [TAP]) (Harris, 1989), which includes acetate as a reduced carbon source, incubated under continuous medium light (75 µmol·m^-2·s^-1) at 25°C.

Representative RNA gel blots for seven chloroplast genes, as well as nuclear (psaG and PSI) and mitochondrial (cob and apocytochrome b) examples, are shown in Figure 1 . The chloroplast genes for which results are shown include one from each of the six categories of plastid transcripts (the ATP synthase complex [atpB]; the cytochrome b₆/f complex [petB]; PSI [psaB]; PSII [psbF], gene expression proteins [tufA and rpl2]; and other functions [cemA, an envelope transporter]) (Rolland et al., 1997). The total RNA samples were pooled from three independent cultures, and after blot hybridization with the probes listed above, the radioactivity was allowed to decay and rehybridization was performed with the chloroplast 16S rRNA gene as a loading control. Because it was possible that 16S rRNA levels might themselves fluctuate, hybridizations also were performed with a cytosolic 25S rRNA probe. The results showed <5% variation between the 25S rRNA and the 16S rRNA signals across all conditions, consistent with the typically high stability of rRNAs (data not shown). Therefore, all results were normalized to the 16S rRNA signal.

View larger version (111K): [in this window] [in a new window]   Figure 1. Representative Chloroplast, Mitochondrial, and Nuclear Transcript Accumulation under Different Culture Conditions. (A) RNA gel blots contained total RNA (10 µg/lane) isolated from cells grown in 500-mL liquid cultures under 12 different culture conditions. Temperature was 25°C unless stated otherwise, and conditions were as follows: C, complete medium (TAP) under continuous light; ML, cells harvested during the middle of the light cycle from a synchronous culture; MD, cells harvested during the middle of the dark cycle from a synchronous culture; BL, TAP medium under high light (300 µE·m-2·s-1); D, dark grown for 72 h; -N, medium lacking nitrogen; -P, medium lacking phosphate; -S, medium lacking sulfate; M, photoautotrophic conditions (minimal medium); L, cells grown at 10 to 12°C for 48 h; H, cells grown at 37°C for 48 h; and UV, TAP medium under continuous light supplemented with 60 mJ·m-2·s-1 UV light (254 nm) for 24 h. Blots were hybridized initially with the experimental probes shown at left (atpB, petB, etc.), quantified and allowed to decay, and probed subsequently with 16S rDNA as a loading control. (B) Variation in transcript species from two gene clusters under different culture conditions. The gels and culture conditions were as described for (A). The cemA-hybridizing species are labeled according to a previously established nomenclature (Drapier et al., 1998). An additional larger transcript (8.5 kb) is denoted by the asterisk; its size was consistent with the inclusion of the atpF coding region. Two transcripts are marked in the rpl2 panel: the polycistronic transcript, which includes the chlL gene (1), and a transcript that is present only during high-temperature culture conditions (asterisk).

View larger version (65K): [in this window] [in a new window]   Figure 2. Transcript Accumulation for Six Classes of Genes. The x axis is labeled by culture condition, using the same symbols used in Figure 1. The y axis shows the percentage change in transcript accumulation relative to cells grown in TAP medium (0 = no change relative to TAP). Each value was the result of three independent RNA isolations pooled into one sample. The genes are color coded, as designated within each panel, and arranged along the z axis for each growth condition. (A) Genes encoding proteins of the ATP synthase complex. (B) Genes encoding proteins of the cytochrome b6/f complex. (C) Genes encoding PSI proteins. (D) Genes encoding PSII proteins. (E) Genes encoding conserved proteins (ycf). (F) Genes encoding miscellaneous proteins. Values exceeding the y axis are shown along the top and are color coded according to the gene they represent.

Genes Encoding Members of a Complex Can Have Concerted Responses
To gain a more complete understanding of transcript abundance under different growth conditions, we used the graphic representation shown in Figure 2. In this figure, transcript accumulation is plotted on the y axis as the percentage change from the control (TAP medium), the x axis shows the different culture conditions, and the color-coded genes are arranged along the z axis. The purpose of this depiction is threefold. First, it reveals any coregulation of transcripts encoding subunits of the same complex, because the results are shown by functional groups of genes (e.g., ATP synthase in Figure 2A). Second, it illustrates whether any functional groups of genes are subject to greater variability (e.g., cytochrome b₆/f complex RNAs appear to vary more than PSII genes). Third, to determine whether changes in plastid transcript levels correlated with changes in their nucleus-encoded counterparts, we examined at least two nuclear genes encoding components of each complex (for a complete list of genes, see Table 1). These data are displayed in Figure 2 for ATP synthase, cytochrome b₆/f, PSI, and PSII (Figures 2A to 2D, respectively) along with genes encoding three conserved chloroplast proteins (Figure 2E) and eight miscellaneous chloroplast proteins (Figure 2F).

Another way to look at these data is to ask whether genes that encode a particular complex exhibit similar profiles. For ATP synthase (Figure 2A), data were scattered except for bright light (BL), for which modest decreases were seen for all mRNAs compared with the control. For the cytochrome b₆/f complex (Figure 2B), nearly uniform increases were seen under three conditions: middle of the light period in synchronized cells (ML), low temperature (L), and exposure to UV light. PSI transcripts (Figure 2C) were particularly concerted, showing decreases under bright light (BL), in the dark (D), in -S, and under heat stress (H). PSI transcripts increased in -P. PSII transcripts (Figure 2D) also increased uniformly in -P and decreased nearly uniformly in the dark (D), in -N and -S, in minimal medium (M), and in heat stress (H). This result is consistent with regulatory elements or factors that recognize classes of genes or RNAs and has an evident functional logic.

Under the conditions tested, we never observed the complete disappearance of any chloroplast transcript, and values usually were within twofold to threefold of the control. On the other hand, 15 chloroplast transcripts exhibited at least a two-thirds reduction under at least one condition, and 4 chloroplast transcripts (cemA, psbC, psbK, and rpl23) exhibited at least a two-thirds reduction under at least four conditions. Exceptional increases were shown by clpP and tufA, particularly under nutrient stress. The tufA mRNA also exhibited increased abundance in the dark, as reported previously (Silk and Wu, 1988). Because clpP and tufA are involved in proteolysis and translation, respectively (Hwang et al., 1996; Majeran et al., 2000), these may be symptomatic of a post-transcriptional plastid stress response mechanism.

To determine whether mitochondrial transcripts also were responsive to culture conditions, we used probes for two genes, cob and coxI. We limited the survey to these two genes because available data suggest that the linear genome consists of only two transcription units (Boer and Gray, 1988; Duby and Matagne, 1999). Interestingly, mitochondrial and chloroplast mRNAs showed opposite effects during nitrogen limitation, in which abundance was significantly higher than in TAP medium (101 and 142%) for cob and coxI, respectively (Figure 1; see also supplemental data online). The mitochondrial transcripts also changed sharply after exposure to 12°C for 24 h, and their response to phosphate limitation was substantial as well (67 and 210% increases). These results suggest that Chlamydomonas chloroplasts and mitochondria have similar yet organelle-specific controls on RNA abundance under abiotic stress conditions.

Having observed large differences in mRNA abundance between control cells and those grown under other conditions, it was important to confirm that these observations did not simply reflect an altered amount of RNA per individual cell. To do so, we obtained growth curves under five culture conditions, as shown in Figure 3A . As expected, cells grown under ideal conditions (TAP [C]) doubled most rapidly, every 5 to 6 h. Cells grown in low-phosphate medium (-P) doubled approximately as fast as dark-grown cells (D), whereas those grown in medium lacking acetate (M) or limited for sulfur (-S) divided very slowly. RNAs were isolated from 1 x 10⁷ cells at selected points during a 2-day time course, in accordance with the 48-h time point used for the samples analyzed in Figures 1 and 2. RNAs from equal numbers of cells were loaded in a gel and either stained for 25S rRNA or probed to identify the 16S rRNA. As shown in Figure 3B, little variation was seen for 16S rRNA over the time course between TAP, -P, and -S cells. 25S rRNA may have decreased slightly; however, the differences are within the range expected from inevitably variable yields in RNA preparations. Because the data in Figure 2 were based on normalization to 16S rRNA, the important conclusion from Figure 3 is that this was an appropriate basis for examining mRNA abundance.

View larger version (31K): [in this window] [in a new window]   Figure 3. Growth Curves and RNA Levels on a per Cell Basis. (A) Graph illustrating cell concentration (y axis) versus time (x axis) for the five different culture conditions shown at right, using the designations used in Figure 1. Values and standard errors are from three replicates. (B) Gel blot analysis of RNAs isolated from the time points shown at top during growth curve experiments in complete (C), -P, and -S media. rRNA panels show the ethidium bromide–stained 25S band; the 16S panels show hybridization of the plastid 16S rRNA. Each lane contained RNA from an equal number of cells.

View larger version (46K): [in this window] [in a new window]   Figure 4. Differential RNA Accumulation in -S and -P Media, as Measured by Microarrays. (A) The top shows a hierarchical cluster analysis showing averages of three independent experiments in which cells were grown in medium lacking sulfate and harvested at 8, 16, or 48 h. After 48 h, cells were transferred back into complete medium for 1 h (R). Green represents mRNAs that exhibited lower abundance than the control (TAP medium), and red represents mRNAs that had higher abundance than the control. A scale is shown at bottom. Enlarged clusters show mRNAs that increased under sulfur limitation (top) and those that rebounded during the replenishment period (bottom). The inset shows RNA gel blot data for two selected genes. The bottom shows a scatterplot for the 48-h time point, where the x axis is the log of the signal intensity (three replicates of three spots each) for transcripts from TAP-grown cells and the y axis is the log of the signal intensity from transcripts from -S grown cells. Numbers (+5, +2, -2, -5) represent fold changes as measured by quantified microarray data, where a twofold change on the array is equal to a 100% difference on RNA gel blots. Black squares represent nuclear genes, blue diamonds represent chloroplast genes, and orange diamonds represent mitochondrial genes. (B) The top shows a hierarchical cluster analysis showing averages of three independent experiments in which cells were grown in medium lacking phosphate and harvested at 8, 24, and 48 h. After 48 h, the culture was supplemented with 2 mM phosphate, and cells were harvested after an additional 1 h (R). The enlarged view is of the dominant cluster in which 33 of 35 members are plastid transcripts. The nuclear Psr1 gene is marked with an asterisk. The bottom shows a scatterplot of the 48-h time point, with labeling as in (A).

The overall effects of nutrient depletion can be seen in the scatterplots. The 45 nuclear genes (black squares) exhibited substantial variation under sulfur limitation (Figure 4A), whereas phosphate limitation resulted in nearly all of our selected nuclear genes (with the exceptions of Psr1 and PetC) remaining within twofold of the control (Figure 4B). Chloroplast genes (blue diamonds) mostly had neutral to decreased transcript levels in -S, but they had increased levels in -P. Mitochondrial transcripts (orange diamonds) exhibited occasional variation. These results confirm and extend those shown by RNA gel blot analysis, in particular the nearly global response of chloroplast transcripts to phosphate limitation.

To gain a more detailed understanding of the chloroplast response to sulfate or phosphate limitation, we repeated these experiments using additional time points and a replenishment period (restoration of P or S to the culture for 1 h). Cells were grown as described in Methods, and samples were removed at 8, 16, and 48 h for -S or at 4, 24, and 48 h for -P. After 48 h, cells were transferred to complete medium and allowed to recover for 1 h before RNA was extracted. Selected RNA gel blots (Figure 4, insets) show the correlation between microarray analyses and filter hybridizations. Data from the microarrays were collected, normalized as described above, and used to generate hierarchical cluster diagrams. Cluster analysis for -S revealed three primary expression profiles. One cluster included the majority of chloroplast genes, for which RNA abundance decreased over time and failed to recover fully to control levels during the replenishment period. A second cluster (expanded at the top of Figure 4A) included 10 nuclear genes and 2 chloroplast genes (atpH and ycf12) that were overabundant (compared with complete medium) during sulfur limitation and declined during replenishment. The third cluster consisted primarily of chloroplast transcription/translation RNAs, which exhibited a reduction during sulfur limitation but recovered upon replenishment (expanded at the bottom of Figure 4A).

The -P time course revealed a complex pattern. At 8 and 24 h, >30 chloroplast transcripts decreased relative to the control; however, by 48 h, these same RNAs had become overabundant (expanded in Figure 4B). This abundance decreased by various amounts during replenishment, by which time 15 chloroplast RNAs had returned to control levels. These rapid changes are consistent with post-transcriptional controls being overlaid on generally less responsive transcriptional mechanisms.

Run-On Assays Reveal Roles for Transcriptional and Post-Transcriptional Control
Because both RNA gel blots and DNA microarrays measure steady state transcript levels, differences observed between samples cannot be ascribed immediately to transcriptional versus post-transcriptional regulation. Therefore, we performed run-on transcription assays by permeabilizing cells using freeze-thaw cycles, followed by a short incubation in the presence of -³²P-UTP to extend previously initiated transcripts (Gagne and Guertin, 1992). RNAs thus labeled are used as probes on DNA gel blots, giving a measure of transcription activity for that gene. In the case of nutrient limitation responses, we expected that if the RNA decreases during sulfur limitation were caused by reduced transcription, this effect would be mirrored in the run-on assay. Similarly, phosphate limitation–induced RNA accumulation would be reflected in increased transcription rates if it were controlled transcriptionally, whereas if the response were attributable to increased RNA stability, the run-on assays would resemble the control (cells grown in TAP).

For run-on assays, the same 143 probes arrayed onto slides were spotted onto nylon membranes. Because genes with low transcription rates might not give signals above background, we first determined how many of the 142 probes could be quantified under our experimental conditions; we found that 104 targets yielded signals above the negative control for several independent TAP-grown samples. The information from the TAP medium could be used immediately to estimate relative plastid promoter strengths by comparison with the well-characterized atpA promoter (Drapier et al., 1998), which is most often used for the aadA selectable marker cassette (Goldschmidt-Clermont, 1991). Mitochondrial values were related to cob. Table 1 shows deduced promoter strengths for the 102 genes that gave values above background. Values for plastid promoters ranged from >90% less than atpA to twofold greater (rbcL). Overall, atpA has a strong promoter, with few genes having transcription rates 125% of its level. Those that did included the ribosomal operon, four PSII genes (psbA to psbD), tufA, and rbcL. These results correlated with previous in vivo measurements obtained by Blowers et al. (1990). Mitochondrial transcription rates varied from >90% less than cob to 18% more than cob. As expected, cob, nad4, and nad5 had similar rates because they originate from the same transcription unit (Remacle and Matagne, 1998).

To address transcriptional versus post-transcriptional control during nutrient limitation, run-on assays were performed for cells grown in -N, -S, and -P for 48 h. Chloroplast transcription rates in -N cells were reduced compared with those in the control sample; however, mitochondrial rates were similar to those of the control (see supplemental data online). Figure 5A shows quantified data from -S and -P samples. When cells were harvested from -S medium (Figure 5A, top), a large decrease in chloroplast transcription rates was observed. Overall, 46% of the chloroplast genes had rates reduced by fivefold or more compared with the control (blue diamonds). By contrast, only three genes had rate increases of twofold or more than the control: the sulfur- responsive genes Ars1 and Sac1 and cab2 (black squares). Figure 5B shows representative primary data (cf. columns C and -S). These results support the hypothesis that the decreases in chloroplast transcript abundance during sulfur limitation result at least in part from lower transcription rates. To confirm that sulfate was the regulator of this response, cells that had been starved for 48 h and then returned to complete medium for 1 h were analyzed in the same manner (Figure 5B, column SR). These sulfur-replenished cells exhibited a dramatic transcriptional recovery, with rates averaging twice those of the control cells (Figure 5B, column C).

View larger version (63K): [in this window] [in a new window]   Figure 5. Transcription Rates as Measured by Run-On Analysis. (A) Scatterplots showing transcription rates for cells grown in TAP medium versus those grown for 48 h in medium lacking sulfate (top) or phosphate (bottom), averaged from two independent experiments. Labeling is as for the bottom of Figure 4. (B) Selected primary data illustrating the decrease in transcription rates during limitation (-S and -P) and their revival after 1 h of nutrient replenishment (SR and PR). Complete data sets are available (see supplemental data online). Chloroplast genes are shown in blue, mitochondrial genes are shown in orange, and nuclear genes are shown in black.

Phosphate Limitation Increases Chloroplast RNA Half-Lives
The combined microarray and run-on data suggested that phosphate limitation increased the stabilities of at least some chloroplast RNAs. To validate this hypothesis, selected RNA half-lives were measured in vivo. When Chlamydomonas is grown in the presence of the antibiotic rifampicin, the -subunit of the PEP is altered irreversibly, inhibiting chloroplast transcription (Surzycki and Shellenbarger, 1976; Eberhard et al., 2002). Therefore, we cultured cells in complete or -P medium and added rifampicin after 48 h; then, we harvested 10 1-h aliquots for RNA extraction and gel blot analysis. As shown in Figure 6 , we measured the half-lives of atpB and petB RNAs. The atpB mRNA exhibited a substantial increase during phosphate limitation (Figures 1A and 2A). Although petB mRNA abundance did not change to the same degree, the transcription rate for petB decreased 51% upon phosphate deprivation, suggesting that this RNA also was more stable under these growth conditions. To account for variations in RNA loading, a rifampicin-insensitive mitochondrial transcript, cob, was used as a loading control. After normalization to cob, the half-lives of atpB and petB transcripts in TAP were found to be 46 and 65 min, respectively, whereas in -P, the half lives increased to 85 and 105 min. These data further support greater RNA stability as a mechanism for increasing chloroplast RNA pools in phosphate-limited Chlamydomonas cells.

View larger version (69K): [in this window] [in a new window]   Figure 6. Analysis of Chloroplast RNA Half-Lives in Phosphate-Limited Cells. The gels at top show RNA gel blot hybridizations (10 µg/lane of total RNA) for cells grown in TAP or for 48 h in -P medium, followed by the addition of 300 µg/mL rifampicin and harvest at 0, 0.5, 1, 2, 4, 6, 8, or 10 h. The atpB and petB coding regions were used in initial hybridizations, followed by the mitochondrial cob gene, a rifampicin-insensitive transcript, as a loading control. The graphs at bottom illustrate the percentage of atpB or petB RNA remaining over the 10-h time course relative to that of cob RNA. Half-lives are shown for each gene and were calculated by linear regression analysis of the data points.

Cells were incubated with two transcription inhibitors during run-on transcription assays. These were a PEP-specific inhibitor, tagetitoxin (Mathews and Durbin, 1990), and a whole-cell transcription inhibitor, actinomycin D. If chloroplast RNAs were transcribed by dual polymerases, tagetitoxin would fail to eliminate all chloroplast signals, because some genes still would be transcribed by the NEP; unfortunately, no NEP-specific inhibitors are available. Figure 7 shows the results of these experiments, along with a control reaction lacking inhibitors. It should be noted that because each experiment was performed with the same number of cells, the entire labeling reaction was added to the hybridization, and because each blot was treated (hybridized, washed, and exposed) in the same way, the images, which were exposed for equal amounts of time, give a fair representation of the relative transcription rates.

View larger version (60K): [in this window] [in a new window]   Figure 7. Run-On Transcription Analysis in the Presence of Transcription Inhibitors. (A) Cells were grown in liquid culture to mid-log phase, harvested and resuspended to 1 x 107 cells/mL, and allowed to grow for 2 h under standard conditions. Cells were harvested and prepared for run-on transcription as described in Methods. Run-on transcription assays were performed with the addition of 30 µL of cells, 1 µL of 100% ethanol (control), 50 units of tagetitoxin, or 100 µg/mL actinomycin D and allowed to transcribe for 30 min at room temperature. Selected genes highlighted on the control and tagetitoxin filters are as follows: black triangles, chloroplast rRNA genes; gray triangles, other chloroplast genes; circles, mitochondrial genes; squares, nuclear genes; X, negative controls. The percentage inhibition for each gene is given in Table 1. Each spot contained 50 ng of DNA, and loading was confirmed by hybridization with a vector probe (data not shown). (B) Gene-specific PCR products representing chloroplast (23S and 16S), mitochondrial (S4 and L7), or nuclear (18S) rRNAs were filter blotted and probed with run-on transcripts as described for (A).

To determine whether the 23S and 16S rRNA hybridization that occurred with RNAs labeled in the presence of tagetitoxin was the result of cross-reactivity with mitochondrial rRNAs, we used the same run-on products to probe filter blots of PCR products specific to the chloroplast or mitochondrial rRNAs; the full genes have regions of substantial similarity. In this experiment, only faint hybridization was visible with the 23S product, and no hybridization was seen with the 16S product (Figure 7B), whereas the mitochondrial and nuclear rRNAs hybridized with and without the inhibitor. Together, these data support a lack of NEP activity in Chlamydomonas chloroplasts.

Novobiocin Modifies Chloroplast RNA Abundance and Transcription Rates
A final question regarding the Chlamydomonas transcriptome involved the potential role of intergenic repetitive elements in influencing the transcription of flanking genes. It is well known that RNAP access to promoter regions can influence transcription initiation rates. In vascular plant plastid genomes, it was reported that the RNAP has a preference for supercoiled templates in vitro, suggesting that DNA structure may be a key factor in establishing basal transcription rates (Lam and Chua, 1987; Zaitlin et al., 1989). In Chlamydomonas, it was observed previously that the addition of a DNA gyrase inhibitor, novobiocin, resulted in altered transcription of petA (Thompson and Mosig, 1987). The putative control element characterized by Thompson and Mosig, the pA repeat, later was found to be ubiquitous throughout the plastid genome (Maul et al., 2002), although it lacks any obvious features such as promoter-like elements. With the availability of chloroplast gene arrays, we wished to determine if novobiocin had a global effect on chloroplast transcription or if it affected only selected regions (e.g., where pA repeats closely flanked known promoters).

For these experiments, cells were grown in TAP medium to log phase (2 x 10⁶ cells/mL), at which time novobiocin was added, and growth was continued for 24 h (Thompson and Mosig, 1987). These cultures were used for both DNA microarray and run-on transcription assays, as shown in Figure 8 . Overall, the addition of novobiocin resulted in the most dramatic expression profile and run-on transcription variation observed for any experiment among those reported here. For many chloroplast genes, the increased abundance seen in arrays (Figure 8A) could be correlated with an increased transcription rate (e.g., atpB and chlB; Figure 8B); however, other chloroplast genes failed to respond in a similar manner (e.g., psbB showed decreased transcription without decreased abundance). Additionally, every mitochondrial gene on the array that exhibited an increase in RNA abundance failed to show higher transcription rates. A sample of the quantified values is presented in Figure 8C, where solid bars show RNA abundance changes and hatched bars show altered transcription rates. Only psaJ showed a transcription rate response akin to that of petA, although several genes did exhibit moderate changes in rate. Together, these data suggest that novobiocin can influence multiple regions in the chloroplast genome and also the mitochondrial genome; however, there is no obvious correlation between the presence of pA repeats, which are widespread, and transcriptional stimulation. The lack of complete correlation between RNA accumulation and transcription rates is not surprising and implies a certain amount of post-transcriptional control.

View larger version (48K): [in this window] [in a new window]   Figure 8. Novobiocin Alters Organelle Transcript Accumulation and Transcription Rates. (A) Pseudocolored DNA microarray showing changes in RNA abundance after exposure of cells to novobiocin (100 µg/mL) for 24 h. Control RNA was reverse transcribed in the presence of Cy3 (green); RNA from novobiocin-treated cells was reversed transcribed in the presence of Cy5 (red). Yellow ovals indicate rRNA genes. (B) Run-on transcription assays of control cells (top) and novobiocin-treated cells (bottom). Ovals in (A) correspond to spots indicated on the novobiocin dot blot. Blue lines denote chloroplast genes with altered expression after novobiocin treatment. Both accumulation and transcription increased for atpB and chlB, whereas atpA exhibited decreased accumulation and transcription. Orange lines indicate two mitochondrial genes for which RNA abundance increased but transcription rates decreased. (C) Fold changes in abundance (solid bars) versus transcription rates (hatched bars) for selected genes. The black bar at left represents the 25S control, blue bars represent chloroplast genes, and orange bars represent mitochondrial genes. See supplemental data online at http://bti.cornell.edu/bti2/chlamyweb/ for a complete data set.

	DISCUSSION

TOP Abstract INTRODUCTION RESULTS DISCUSSION METHODS References

The opportunity for a genome-wide transcription analysis arose after the completion of the plastid sequence in our laboratory (Maul et al., 2002) and allowed us to compare transcription statistics from Chlamydomonas with those of several other organisms with sequenced plastid genomes. Table 2 shows that relative to a representative group of organisms that includes red and green algae and lower and higher plants, Chlamydomonas possesses the largest plastid genome, yet it is relatively gene poor. This increased genome size is not the result of gene duplication or intron accumulation, as has occurred in Marchantia and tobacco; instead, it is caused by repetitive DNA accumulation (Maul et al., 2002). Like Chlorella, Chlamydomonas lacks the seven NADH dehydrogenase genes; it also lacks the accD gene encoding an acetyl CoA carboxylase subunit, which is present in all other sequenced chlorophyte and streptophyte plastid genomes, and at least five other genes present in Chlorella, resulting in the most gene-poor chlorophyte plastid reported to date. However, sequences homologous with five of these missing genes (AccD, CysA, FtsH, InfA, and MinD) have been identified in the Chlamydomonas EST database (http://www.biology.duke.edu/chlamy_genome/), indicating that they have been transferred functionally to the nuclear genome.

View larger version (25K): [in this window] [in a new window]   Figure 9. The Chlamydomonas Plastid Transcriptome. The outer circle diagrams the transcribed regions, with those in black corresponding to monocistronic RNAs and those in gray corresponding to polycistronic RNAs or complex transcription units. The extents of many transcripts are approximate because the 5' and/or 3' ends have not been mapped precisely. The rpoC2 gene is shown as punctually transcribed based on reverse transcriptase PCR data presented elsewhere (Maul et al., 2002). Genes are color coded by function: yellow indicates cytochrome b6/f, blue indicates PSI, green indicates PSII, red indicates ATP synthase, orange indicates ribosomal and RNA-associated genes, black indicates tRNAs, and purple indicates other classes and genes of unknown function.

Chloroplast RNA responses to shifts in light quality and quantity have been reported previously (Salvador et al., 1993; Kloppstech, 1997). However, in angiosperms, these initial findings were shown to be attributable primarily to shifts in RNA polymerase activity in response to light-stimulated developmental changes (Pfannschmidt and Link, 1997; Oikawa et al., 1998; Krause et al., 2000; Singh and Singhal, 2001). If these effects are excluded, there are few published studies emphasizing a direct role of environmental stimuli on organelle gene regulation, although two of these have been conducted using Chlamydomonas (Salvador et al., 1993; Hwang et al., 1996). Here, we have demonstrated that under laboratory-induced stress, Chlamydomonas modulates transcript levels in both the plastid and the mitochondrion. Transcript abundance as measured by both RNA gel blot and DNA microarray analysis revealed that nutrient stress and exposure to UV light caused the most consistent changes across the genome as well as the largest overall changes in transcript levels.

To determine if chloroplast protein levels were affected by the observed changes in RNA levels, immunoblot analysis was performed for selected chloroplast proteins. These experiments showed only minor changes in protein levels (data not shown), with -S cells having a slight reduction in total protein; however, relative levels of individual protein were unaffected. In the future, proteomic methods would be valuable in showing how changes in transcript levels are reflected in the organellar proteomes under stress conditions. It also would be desirable to measure translation rates directly by pulse labeling, to determine whether changes in available RNA alter rates of protein synthesis. However, pulse labeling in Chlamydomonas has not been successful under stress conditions.

A Role for Nutrients in Organellar Gene Regulation
How can the physiological changes that occur during nutrient limitation be linked to our observations regarding chloroplast gene expression? In both sulfur and phosphate deficiency, cells deprived of the nutrient quickly induce a scavenging system and make metabolic adjustments. When sulfur is limited, proteins such as arylsulfatases are secreted, and there is an inhibition of protein synthesis that is correlated with an increase in the accumulation of organic nitrogen (reviewed by Marschner, 1995). This decrease in protein synthesis leads to chlorosis and a specific reduction in proteins that have higher proportions of Met and Cys. Under phosphate limitation, phosphatases are secreted, and there is a mobilization of internal stores, for example, through the activation of cytosolic ribonucleases (reviewed by Green, 1994). Phosphate-limited growth also is characterized by a depressed rate of starch synthesis; however, total carbon fixation is increased (reviewed by Marschner, 1995). Phosphate and sulfur limitation have similar effects on photosynthetic electron transport. Chlorophyll levels decline, PSII function is decreased, and light harvested by the light harvesting complex II is lost as heat or possibly directed to PSI (Wykoff et al., 1998).

The effects of these two stresses have been well studied in Chlamydomonas (reviewed by Grossman, 2000). For example, there is a marked decline in photosynthesis during suboptimal growth conditions, which is critical to cell viability (Wykoff et al., 1998). During sulfur limitation, the cells quickly reduce photosynthesis rates below that of respiration, and the levels of the photosynthetic proteins encoded by psbA, rbcL, and psaA are reduced greatly after 48 h (Zhang et al., 2002). During phosphate limitation, both Chlamydomonas and the green alga Selenastrum minutum exhibit shifts in photosynthetic activity toward the fixation of carbon for storage versus for respiratory metabolism (Ball et al., 1990; Theodorou et al., 1991). Our results showing marked changes in organellar RNA profiles during abiotic stress complement these previous studies, mainly in that physiological changes not only are correlated with gene regulation in the nucleus but also directly affect the energetic centers.

Run-on transcription analysis showed that sulfur and phosphate limitation had different effects on transcription rates (Figure 5). Sulfur limitation reduced rates by 2- to 10-fold for both chloroplast and mitochondrial genes, consistent with diminished RNA accumulation. When sulfate was replenished, transcription recovered; it was stimulated particularly for a group of chloroplast genes involved in transcription or translation. It would be interesting to determine whether the translational apparatus responds as rapidly as the transcriptional apparatus under these conditions. During phosphate limitation, rates decreased up to 80% of the control rate after 48 h. Because we concomitantly observed increased transcript accumulation, this suggested, and we later confirmed, that changes in at least some RNA levels were a result of increased stability (Figure 6). The mechanism for decreased transcription rates under sulfur limitation could be part of a general metabolic slowdown or could result from a specific signaling cascade. For example, it has been postulated that the mustard chloroplast RNAP can be regulated by reversible phosphorylation of its sigma factors (Tiller and Link, 1993).

A limited role for transcriptional regulation in the chloroplast has long been postulated (Deng and Gruissem, 1987), and we found that phosphate limitation nearly doubled the half-lives of atpB and petB mRNAs. Phosphate stress is a particularly interesting context in which to study chloroplast RNA regulation. Recent models for chloroplast RNA degradation suggest a two-step process in which initial endonucleolytic cleavages are followed by the addition of poly(A)-rich tails, which in turn lead to rapid decay (Schuster et al., 1999; Monde et al., 2000). Although the endonucleases have not been identified definitively, it is likely that polynucleotide phosphorylase (PNPase) is responsible for removing the poly(A) tail and upstream sequences. Polyadenylation-mediated chloroplast RNA decay has been demonstrated clearly in spinach in vitro (Kudla et al., 1996; Lisitsky et al., 1997) and in Chlamydomonas both in vitro and in vivo (Komine et al., 2000, 2002). Most interestingly, it was shown recently that like its bacterial counterpart, spinach chloroplast PNPase has both poly(A) polymerase and 3' to 5' exoribonuclease activities (Yehudai-Resheff et al., 2001). In these in vitro assays, the activity of PNPase could be directed to RNA degradation or polymerization by manipulating physiologically relevant concentrations of Pi and ADP. Pi significantly enhanced degradation, whereas ADP inhibited degradation and enhanced polymerization. Thus, phosphate limitation could cause a reduction of PNPase-mediated degradation activities.

Dependence on a Single RNA Polymerase May Be Reflected in Environmental Sensitivity
In surveying the transcriptional response, we used both a PEP-specific inhibitor, tagetitoxin, and a global transcriptional inhibitor, actinomycin D (Figure 7). Because tagetitoxin appeared to inhibit all transcription, we tentatively conclude that the Chlamydomonas chloroplast lacks a NEP. This conclusion is supported by a recent study in which the addition of another PEP inhibitor, rifampicin, resulted in the reduction of transcription rates for four genes when cells were cultured in TAP medium and for five genes when cells were grown in minimal medium (Eberhard et al., 2002). If Chlamydomonas chloroplasts lack a NEP, this would be a unique situation. Chloroplast-targeted NEPs are known in several land plants and in the moss Physcomitrella (Kabeya et al., 2002; Richter et al., 2002). It is possible that photosynthetic organisms that fail to undergo the complex process of plastid biogenesis, particularly unicellular organisms, generally lack the NEP, suggesting a putative evolutionary role in its acquisition or maintenance.

	METHODS

TOP Abstract INTRODUCTION RESULTS DISCUSSION METHODS References

 
Chlamydomonas Strains and Culture Conditions
Chlamydomonas reinhardtii (CC-125 mt⁺) was maintained on 0.8% Tris-acetate-phosphate (TAP) agar (Harris, 1989) at 25°C under constant light (70 µE·m^-2·s^-1). For RNA isolation, a sample of cells was placed into 50 mL of liquid TAP medium and allowed to grow under continuous light at 25°C on a rotary shaker (125 rpm) to mid-log phase (1 x 10⁷ cells/mL). This starter culture then was harvested by centrifugation, washed with appropriate liquid medium, transferred to 500 mL of the desired culture medium, and placed in the appropriate culture condition (see figure legends). Five culture media were used: complete medium (TAP), minimal medium lacking acetate (M) (Harris, 1989), medium without nitrogen (-N), medium without phosphate (-P [Shimogawara et al., 1999]), and medium without sulfate (-S [Yildiz et al., 1996]). Cells were harvested at 24 h (UV light treatment), 48 h (-P, -N, -S, minimal medium, light treatment, and heat treatment), or 72 h (dark treatment and bright-light treatment) after transfer. For analysis of synchronized cells, 50 mL of starter culture was transferred to 500 mL of minimal medium and grown under a 14-h-light/10-h-dark cycle for 5 days. On day 6, half of the culture was collected during the middle of the light period, and the remaining half was collected during the middle of the dark period. For each culture condition, a minimum of three independent samples (each originating from a different starter culture) were tested for RNA quality via hybridization and pooled for subsequent analyses.

Growth curves were obtained by harvesting cells grown in TAP medium for 24 h under standard conditions, washing once with sterile water, and adding 2 x 10⁵ cells to 500 mL of each culture medium assayed. Cells were counted at seven time points (4, 8, 12, 16, 24, 48, and 72 h) using a hemacytometer, and the appropriate amount of culture was harvested to yield 1 x 10⁷ cells.

RNA Gel Blot Analysis
Total RNA isolation, electrophoresis, blotting, and hybridization were performed as described previously (Drager et al., 1998). RNA from growth curves was resuspended in 50 µL of sterile water, and 10 µL was loaded per lane. RNA for microarray analysis was processed further with the addition of 10 units of DNase (Promega, Madison, WI) per microgram of RNA and incubation at 37° for 0.5 h, followed by the addition of 1 volume of 4 M LiCl and incubation on ice for 30 min. RNA was collected by centrifugation and washed twice with 70% ethanol. For RNA gel blot hybridizations, the experimental probe was hybridized first, images were captured on a Storm 840 phosphorimaging system, and band intensity was quantified using Image Quant version 1.2 software (Molecular Dynamics, Sunnyvale, CA). Membranes were placed at -80°C for 2 months and then rehybridized with the chloroplast 16S rDNA, which also was quantified, and this information was used for normalization.

Gene Probes
Gene-specific probes were generated for 84 chloroplast genes, 10 mitochondrial genes, and 44 previously characterized nuclear genes. Additional chloroplast probes were generated in newly sequenced regions (Maul et al., 2002) for which expression data had not been collected previously. Primers were designed based on the chloroplast or mitochondrial genome sequence using Oligo 6.1 software (Molecular Biology Insights, Cascade, CO) with the following parameters: each resulting fragment was between 150 and 1500 bp and contained (for known genes) little if any noncoding sequence. Nuclear gene primers were designed based on previously deposited sequences (GenBank accession numbers are listed in Table 2). A complete list of primers is available (see supplemental data online). Probe generation for organelle genes was conducted using standard PCR conditions in the presence of Taq DNA polymerase (Fisher Scientific, Chicago, IL). Reverse transcriptase–mediated PCR was performed using the Access PCR system (Promega) to generate nuclear gene fragments. All PCR products were subjected to agarose gel electrophoresis, their sizes were confirmed using molecular mass standards, and single bands were excised and purified using Qiaex II (Qiagen, Valencia CA) for subsequent cloning into a T-tailed PCR vector (pGEM-T Easy [Promega] or PCR-II [Invitrogen, Carlsbad, CA]). Positive bacterial colonies were selected, and plasmid DNA was extracted. To ensure that the correct insert was cloned, a single pass sequence was performed with vector primers (M13 forward/reverse). Once the sequence was confirmed, inserts were extracted via restriction with EcoRI, gel purified, and used in RNA gel blot hybridizations.

Microarray Construction and Hybridization
DNA microarrays and low-density nylon membranes were generated using the plasmid DNA from the 142 clones described above and in Table 1. Standard PCR was performed for all clones in replicate using universal vector primers (M13 forward/reverse) and Fisher Taq DNA polymerase. Replicates were combined and purified using PCR filter plates (Millipore, Bedford, MA) in a 96-well format. Purified PCR products were resuspended in 20 µL of water, and 1 µL of each product was checked for successful amplification and purity by electrophoresis on a 1.0% agarose gel. PCR was repeated for any clones that failed to yield the desired size or gave weak amplification. Once the full set of 142 clones was determined to be of satisfactory quality, the purified products were diluted with either 20 µL of DMSO or 6 x SSC (1x SSC is 0.15 M NaCl and 0.015 M sodium citrate) and 1.5 M betaine (Sigma) and stored at -80°C until they were arrayed.

DNA microarrays were constructed at the Center for Gene Expression Profiling (CGEP), which is located at the Boyce Thompson Institute. Purified PCR products were spotted in triplicate onto GAPII glass slides (Corning, Corning, NY) using a BioRobotics Microgrid Pro arrayer (BioRobotics, Woburn, MA) with a 16-split-pin spotting tool. Because of the small size of the microarray (3 spots per gene, 426 spots total), it was possible to print two arrays per slide with a 20-mm gap between them. After both arrays were printed, slides were allowed to dry on the stage overnight, cross-linked with 300 µJ of 254-nm UV light, and baked at 80°C for 4 h. Slides then were blocked or stored under desiccation for up to 3 months. Before hybridization, slides were blocked with succinic anhydride according to the manufacturer's directions (Corning), prehybridized at 42°C for 1 h in prehybridization buffer (25% formamide, 5 x SSC, 0.25% SDS, and 0.25% filtered BSA), washed with water, and dried in isopropanol. A total of 20 µL of denatured cDNA probe in hybridization buffer (25% formamide, 5 x SSC, 0.1% SDS, 100 ng/µL sheared salmon sperm DNA, and 1 µL of poly[A] blocker [Invitrogen]) was added immediately after prehybridization, and arrays were covered with 22- x 22-mm Hybri-Slip cover slips (Grace Laboratories, Bend, OR) and allowed to hybridize in sealed chambers (Corning) at 42°C for a minimum of 20 h. Slides were prepared for scanning by removing the cover slip at room temperature in 2 x SSC and 0.25% SDS, followed by a 10-min wash in the same buffer at 42°C with vigorous agitation. The slides were transferred to 0.2 x SSC and 0.1% SDS for 10 min at room temperature, followed by four 2-min rinses in 0.1 x SSC. Slides then were plunged into sterile water for <5 s, rinsed in 100% ethanol, and spun dry.

cDNA Labeling
Fluorescently labeled Cy3 or Cy5 cDNA probes were generated from total RNA using a direct incorporation reverse transcription method. Each experiment (control versus sample) was replicated a minimum of three times, and each was completely independent (from starting material to hybridization), including at least one dye swap per experiment. DNase-treated total RNA (50 µg) was used in each labeling reaction using the method described by Hegde et al. (2000) with the addition of 6 µg of random primers (Invitrogen). Labeled cDNA was passed through PCR purification columns (Qiagen) and eluted with 40 µL of sterile water. Corresponding Cy3 and Cy5 samples were combined and then dried under vacuum. Pellets were resuspended in hybridization buffer, denatured at 95°C for 5 min, and allowed to cool at room temperature for 2 min before adding the probe to the slide.

Array Image Acquisition and Data Analysis
Microarrays were scanned at the CGEP using a confocal laser fluorescent scanner (ScanArray 5000; Packard Instruments) using the Cy3 channel (570 nm) and the Cy5 channel (660 nm) set to 10-µm resolution. TIFF images were saved, and spot intensities were quantified using the TIGR Spotfinder software package (www.tigr.org/softlab). Quantified data were imported into Excel XP (Microsoft, Redmond, WA), and spot replicates were averaged. Any poor spots (defined as spots exhibiting signal of <150,000 units) were removed from subsequent analyses. Based on RNA gel blot analyses, 25S, 23S, and 16S rRNAs failed to show significant accumulation differences under any conditions examined; therefore, the combination of these values was used in those cases in which the Cy3 and Cy5 channels needed to be normalized to account for nonuniform reverse transcription. Any experiment that required normalization greater than twofold was considered to have failed and was repeated. The three (or more) averaged data sets per experiment were merged into a final data set, resulting in a minimum of nine individual data points per gene per experiment. Microarray results also were compared with the previously collected RNA gel blot data and were qualitatively consistent.

Normalized and averaged microarray data were used to generate scatterplots and hierarchical clusters in the TIGR multiple-experiment viewer software package. Each replicate of each experiment (control versus experimental) was visualized in the single-experiment viewer and filtered to exclude spots equal to or less than the negative control spots, resulting in an average of 98 of 142 targets that yielded acceptable signals. Genes showing expression ratios greater than twofold were retained, and data were collected. Quantified data and resulting images are available on the Chlamydomonas chloroplast genome World Wide Web site (http://bti.cornell.edu/bti2/chlamyweb/). The averaged data sets of time points were used in the TIGR multiple-experiment viewer and to generate hierarchical cluster results using the average linkage clustering option, in which only genes were clustered, irrespective of the experiment.

Run-On Transcription Analysis
Nylon filters used in run-on transcription assays were generated using the same PCR products as those spotted onto glass slides. Purified PCR products were diluted to a final concentration of 2 ng/µL in water, and an equal volume of 0.8 M NaOH and 20 mM EDTA was added before denaturation at 98°C for 15 min and placement on ice. A total of 50 µL of each PCR product were transferred to Hybond N⁺ nylon membranes (Amersham Biotech, Uppsala, Sweden) using the Bio-Rad 96-well vacuum dot-blot apparatus according to the manufacturer's directions (Hercules, CA).

Chlamydomonas cells were grown as described above and harvested, and their density was determined. For all conditions, cells were adjusted to 1 x 10⁶ cells/mL, and 50 mL of this dilution was used to prepare cells for run-on transcription. Cells were permeabilized according to Gagne and Guertin (1992), and 30-µL aliquots were stored at -80°C until use. For generation of radiolabeled transcripts, cells were subjected to three freeze/thaw cycles, with some experiments requiring the addition of selected transcription inhibitors (50 units of Tagetin [Epicenter, Madison, WI], 100 µg/mL novobiocin, or 100 µg/mL actinomycin D [Sigma, St. Louis, MO]) during the freeze/thaw cycle. After the last thaw, cells were washed twice in run-on wash buffer. Each reaction contained 30 µL of permeabilized cells, 15 µL of 4 x run-on transcription buffer (Sakamoto et al., 1993), 2 µL of RNase Out RNase inhibitor (Invitrogen), 8 µL of -³²P-UTP, and an inhibitor if required. Reactions proceeded at room temperature for 30 min and were stopped by the addition of 20 µL of 20% SDS and 1 mL of Tri-reagent (Molecular Research Center, Cincinnati, OH). Radiolabeled RNAs were extracted, and unincorporated nucleotides were removed. Hybridization, washing, and quantification were as described for RNA gel blots. Each quantified data set is an average of at least two independently replicated samples.

Transcription rates were measured by taking the average signal for each gene and subtracting the signal produced by negative control spots. Basal transcription rates in TAP medium were measured against the rate of atpA for chloroplast transcripts or cob for mitochondrial transcripts. Comparisons between treatments were made by dividing the average signal of each experimental sample by that of the TAP control sample. Complete data sets and primary data are available at http://bti.cornell.edu/bti2/chlamyweb/.

Upon request, all novel materials described in this article will be made available in a timely manner for noncommercial research purposes. No restrictions or conditions will be placed on the use of any materials described in this article that would limit their use for noncommercial research purposes.

	Acknowledgments

 
We thank Carrie Breehl for providing technical assistance on the project, Paul Debbie for his assistance with microarray experiments performed at the CGEP, and the Cornell BioPL 641 class for enthusiastic participation in early microarray experiments. We also acknowledge Stephan Eberhard and Francis-André Wollman for communicating unpublished results. This work was supported by National Science Foundation Grant MCB 9975765 to D.B.S. and a National Institutes of Health–National Research Service Award postdoctoral fellowship to J.W.L.

	Footnotes

 
Online version contains Web-only data.

Article, publication date, and citation information can be found at www.plantcell.org/cgi/doi/10.1105/tpc.005595.

Received June 21, 2002; accepted September 10, 2002.

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