Transcriptome Changes for Arabidopsis in Response to Salt, Osmotic, and Cold Stress^,

Abstract

To identify genes of potential importance to cold, salt, and drought tolerance, global expression profiling was performed on Arabidopsis plants subjected to stress treatments of 4°C, 100 mm NaCl, or 200 mm mannitol, respectively. RNA samples were collected separately from leaves and roots after 3- and 27-h stress treatments. Profiling was conducted with a GeneChip microarray with probe sets for approximately 8,100 genes. Combined results from all three stresses identified 2,409 genes with a greater than 2-fold change over control. This suggests that about 30% of the transcriptome is sensitive to regulation by common stress conditions. The majority of changes were stimulus specific. At the 3-h time point, less than 5% (118 genes) of the changes were observed as shared by all three stress responses. By 27 h, the number of shared responses was reduced more than 10-fold (< 0.5%), consistent with a progression toward more stimulus-specific responses. Roots and leaves displayed very different changes. For example, less than 14% of the cold-specific changes were shared between root and leaves at both 3 and 27 h. The gene with the largest induction under all three stress treatments was At5g52310 (LTI/COR78), with induction levels in roots greater than 250-fold for cold, 40-fold for mannitol, and 57-fold for NaCl. A stress response was observed for 306 (68%) of the known circadian controlled genes, supporting the hypothesis that an important function of the circadian clock is to “anticipate” predictable stresses such as cold nights. Although these results identify hundreds of potentially important transcriptome changes, the biochemical functions of many stress-regulated genes remain unknown.

Plants have a remarkable ability to cope with highly variable environmental stresses, including cold, drought, and soils with changing salt and nutrient concentrations (i.e. abiotic stress). Nevertheless, these stresses together represent the primary cause of crop loss worldwide (Boyer, 1982), reducing average yields for most major crop plants by more than 50% (Bray et al., 2000). In contrast, the estimated yield loss caused by pathogens is typically around 10% to 20%.

Significant progress has been made to understand and manipulate abiotic stress responses (for reviews, see Shinozaki and Yamaguchi-Shinozaki, 1996; Bohnert and Sheveleva, 1998; Smirnoff, 1998; Blumwald, 2000; Bray et al., 2000; Cushman and Bohnert, 2000; Hasegawa et al., 2000; Knight, 2000; Schroeder et al., 2001; Serrano and Rodriguez-Navarro, 2001; Thomashow, 2001; Zhu, 2001b, 2001a). Three important themes have emerged.

First, the initiation of most stress treatments correlates with a cytosolic calcium release, in some cases with stimulus-specific patterns of oscillation (Allen et al., 2000; Knight, 2000; Posas et al., 2000). Second, stimulus-specific changes in gene expression are often observed alongside a set of shared stress responses. For example, in a survey of 1,300 Arabidopsis genes, the majority of cold and drought stress-regulated genes were observed as a shared stress response (Seki et al., 2001). Together, these observations support the hypothesis that a common set of signal transduction pathways are triggered during many stress responses.

A third important theme is that increased levels of stress tolerance can be engineered into plants by reprogramming the expression of endogenous genes. For example, overexpression of the transcription factor C-BOX BINDING FACTOR-1 (CBF1) resulted in plants with increased tolerance to cold stress (Jaglo-Ottosen et al., 1998). Inducible expression of the transcription factor DEHYDRATION-RESPONSIVE ELEMENT BINDING-1A (DREB1A) also resulted in improved tolerance to several stress conditions, including drought, salt, and cold (Kasuga et al., 1999). These two successes probably resulted from the overexpressed transcription factor altering the expression of many downstream genes. Overexpression of a cold- and drought-inducible calcium-dependent protein kinase gene in rice (Oryza sativa) also up-regulated the expression of several stress-regulated genes and increased drought tolerance in the transgenic rice plants (Saijo et al., 2000). However, in some cases, a stress response can be improved by changing the expression of a single downstream gene. For example, overexpression a Na⁺/H⁺-antiporter gene in tomato (Lycopersicon esculentum) and Arabidopsis provided a dramatic increase in NaCl resistance (Apse et al., 1999), presumably by preventing the build-up of toxic levels of cytosolic Na⁺.

Understanding a plant's response to a stress will require a comprehensive evaluation of stress-induced changes in gene expression. Using oligonucleotide and cDNA microarrays providing a partial coverage of the Arabidopsis genome, expression profiling studies have revealed a large number of changes associated with particular stages of plant development (Zhu et al., 2001), the circadian clock (Harmer et al., 2000), and various stresses such as wounding, cold, and pathogens (Maleck et al., 2000; Schenk et al., 2000; Bohnert et al., 2001; Seki et al., 2001). Expression profiling has also been used to study stress responses in other species, such as salt stress in rice (Kawasaki et al., 2001), barley (Hordeum vulgare; Ozturk et al., 2002), and yeast (Saccharomyces cerevisiae; Posas et al., 2000; Rep et al., 2000; Bohnert et al., 2001; Yale and Bohnert, 2001). A compiled list of genes connected to abiotic stress responses in Arabidopsis and other plants can be viewed at http://stress-genomics.org.

Here, we present mRNA expression profiles of leaves and roots from Arabidopsis subjected to salt (100 mm NaCl), hyperosmotic (200 mm mannitol), and cold (4°C) stress treatments. We used an Arabidopsis GeneChip microarray (Zhu and Wang, 2000), which provided probe sets for approximately 8,100 genes. We had two specific objectives. First, to identify mRNAs that change in a “stress-specific” fashion in response to cold, salt, or hyperosmotic stress. Second, to identify mRNAs that are coregulated during the acute phase (first 3 h) of a shared stress response. This is the first study to compare all three stresses using a global expression profiling strategy. Through a comparison of three different stress treatments, we reasoned that we could better identify both shared and stimulus-specific responses. Our results revealed changes in approximately 30% of the transcriptome present on the GeneChip, with most changes classified as stimulus specific. This global view illustrates the “fluid” nature of the transcriptome and the challenge we face in understanding the complexity of any given stress response.

RESULTS

Using a GeneChip microarray, we identified 2,678 probe sets representing a combined total of 2,409 unique stress-regulated genes that displayed a greater than 2-fold change in expression compared with a fresh medium control. Expression profiles were made separately for roots and leaves isolated from plants exposed for 3 or 27 h to a 100 mm NaCl, 200 mm mannitol, or 4°C stress (Supplemental Table 1, which can be viewed at www.plantphysiol.org).

Non-Stress-Regulated Controls

A set of 10 representative control genes (non-stress regulated) were identified that did not show a significant change in expression under any of the stress treatments (Table I). These examples include commonly used loading controls, such as genes encoding polyubiquitin, eukaryotic initiation factor 4A1 and actin-2. A gene for a V-type H+-ATPase 16-kD subunit provides an example of a moderately expressed gene with similar expression levels in roots and leaves.

Table I.

Representative constitutively expressed controls

Annotation	Expression Levels						Fold Change
	Control						Control
	Leaves			Roots			Leaves	Roots	R/L
	3 h	27 h	Avg	3 h	27 h	Avg	3/27 h	3/27 h	Ratio
Polyubiquitin, UBQ10	4,197	3,803	4,000	4,240	4,811	4,526	1.1	0.9	1.1
Eukcaryotic initiation factor elF-4A1	2,373	2,436	2,405	2,216	2,426	2,321	1.0	0.9	1.0
Aquaporin, PIP-1B	2,087	2,093	2,090	2,298	3,135	2,717	1.0	0.7	1.3
V-type H+-ATPase, 16-kD subunit	1,535	1,780	1,658	1,555	1,899	1,727	0.9	0.8	1.0
40S ribosomal protein S16	1,314	1,550	1,432	1,596	1,791	1,694	0.8	0.9	1.2
Actin 2	1,440	1,267	1,354	2,171	2,316	2,244	1.1	0.9	1.7
Plasma membrane H+-ATPase, AHA1	536	757	647	342	483	413	0.7	0.7	0.6
Tubulin, β-4	575	671	623	804	712	758	0.9	1.1	1.2
Calmodulin-1	331	376	354	749	719	734	0.9	1.0	2.1
Ca-dependent protein kinase, CPK3	127	148	138	250	241	246	0.9	1.0	1.8

Fold Change
4°C				Mannitol				NaCl				Probe Set No.	AGI No.
Leaves		Roots		Leaves		Roots		Leaves		Roots
3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h
1.2	1.2	1.0	1.3	1.4	1.0	0.7	0.9	1.0	1.2	0.9	0.8	12833_f_at	At4g05320
1.0	1.1	1.1	1.1	0.8	1.0	0.8	1.1	0.7	1.1	0.9	1.3	16026_at	At3g13920
1.3	1.2	1.4	1.3	1.4	1.4	1.0	1.3	1.4	1.3	1.2	1.3	15977_s_at	At2g45960
0.9	0.9	1.0	1.0	1.0	1.2	0.9	1.2	1.0	1.1	0.9	1.1	15584_s_at	At1g19910
0.8	0.8	0.9	0.8	0.8	0.9	0.8	1.1	0.7	1.2	0.7	1.1	17390_at	At2g09990
1.3	1.5	1.4	1.2	1.2	1.1	0.9	1.3	0.9	1.0	0.8	1.1	16476_at	At3g18780
0.9	0.6	0.9	0.5	0.8	1.1	1.0	1.1	0.7	1.0	1.0	0.8	14713_s_at	At2g18960
1.0	1.2	1.3	1.6	0.8	0.7	1.0	1.0	1.0	1.0	0.7	1.0	15988_at	At5g44340
0.7	1.1	0.7	1.0	0.7	0.9	0.9	1.0	0.7	1.0	0.7	0.9	15173_f_at	At5g37780
0.9	0.9	1.1	0.9	0.9	1.0	0.7	0.9	0.8	1.3	0.8	1.0	17058_s_at	At4g23650

Identification of Shared and Stimulus-Specific Responses

Figure 1 illustrates the breakdown by stress for the 2,678 probe sets identifying a 2-fold or greater change in expression. It is important to note that our fresh medium control also resulted in 741 changes between 3 and 27 h, of which nearly one-half (407 probe sets) were also affected by stress treatments (Fig. 1).

Figure 1.

Venn diagrams showing an overview of stress-regulated changes (> 2-fold) for different treatment conditions. Stress-induced changes were identified in 2,678 probe sets (which approximately equals the number of genes). The number of changes and the percentage corresponding to up-regulation are shown. Numbers for fresh medium represent a comparison between 3 and 27 h. Numbers for the three stresses represent a comparison with the average of the 3- and 27-h control.

The Venn diagrams shown in Figure 2 illustrate one of the many ways in which this large data set can be sorted to reveal potential insights. These diagrams provide an important overview showing the distribution of changes into shared and stress-specific responses. To provide gene-specific information on the hundreds of shared and stress-specific responses, we have organized 15 supplemental tables (Supplemental Tables 2A–G, 3A–G, and 4; they can be viewed at www.plantphysiol.org), as identified in Figure 2. These tables can be accessed on-line and analyzed with computer software.

Figure 2.

Venn diagrams showing the distribution of stimulus-specific and shared stress responses (> 2-fold). Numbers in italics correspond to probe sets identified in a specific category. Most of these changes were only observed once as a transient change. Non-italicized numbers in parentheses correspond to individual genes that passed a more stringent criterion for reproducibility (see text). Further information on these selected changes can be found in Tables II through V (shown here) or as supplemental information in Supplemental Tables 2A–G and 3A–G (They can be viewed at www.plantphysiol.org).

To illustrate important themes and ways to view the data, four tables were selected for presentation alongside the text. A change was listed in these tables (Tables II–V; Supplemental Tables 2A–G, 3A–G; they can be viewed at www.plantphysiol.org) only if it met several conservative criteria. First, we required all changes to show reproducibility in at least two treatments (e.g. at 3- and 27-h time points, at the same time point in more than one tissue, or at the same time point with at least two stresses). Second, the direction of the change had to be the same for the gene to be labeled as coregulated by more than one stress (e.g. cold and mannitol regulated means induced or repressed in both cold and mannitol). Finally, we required all changes to show reproducibility of a 2-fold change in comparison with both the averaged 3- and 27-h controls as well as with their respective 3- or 27-h individual time-point controls. This was done to filter out changes that were likely attributable only to changes induced in the fresh medium control. The annotation listed for each gene was derived from the Institute for Genomic Research (or AGI) listing. In some cases we provided updated information. Functional annotation is expected to change for many of the genes as experimental information becomes available.

Table II.

Overlap at 3 h in root for cold, mannitol, and NaCl stress

Annotation	Expression Levels						Fold Change at 3 h
	Control			3 h			4°C	Mannitol	NaCl	Probe Set No.	AGI No.
	3 h	27 h	Avg	4°C	Mannitol	NaCl
Low-temperature-induced protein 78	24	24	24	2,351	932	1,356	98.0	38.8	56.5a	15611_s_at	At5g52310
Unknown	24	24	24	60	177	682	2.5	7.4	28.4	14097_at	At2g47770
Late embryogenesis abundant (LEA-like)	24	24	24	86	140	670	3.6	5.8	27.9	19152_at	At5g06760
bZIP transcription factor-like	24	30	27	101	159	279	3.7	5.9	10.3a	13965_s_at	At4g34000
Flavin-containing monooxygenase	53	72	63	996	617	637	15.8	9.9	10.2	18596_at	At1g62570
CHX17, putative Na+/H+-exchanger	24	25	25	92	167	211	3.8	6.8	8.6	13627_at	At4g23700
Unknown	44	45	45	219	90	366	4.9	2.0	8.2	20179_at	At4g38060
Homeobox-Leu zipper protein ATHB-12	38	25	32	144	177	259	4.6	5.6	8.2a	16115_s_at	At3g61890
Unknown	62	100	81	300	317	639	3.7	3.9	7.9a	20042_s_at	At4g34010
Cold- and ABA-inducible protein kin1	716	422	569	2,654	3,994	4,168	4.7	7.0	7.3a	16474_s_at	At5g15960
Cold-regulated protein COR6.6 (KIN2)	729	399	564	2,696	3,804	4,115	4.8	6.7	7.3ab	18701_s_at	At5g15970
Zinc-binding protein, putative	24	24	24	780	113	171	32.5	4.7	7.1	14367_at	At1g60190
β-ketoacyl-CoA synthase, putative	30	58	44	132	264	288	3.0	6.0	6.5	18955_at	At1g04220
Unknown	142	233	188	747	599	1,226	4.0	3.2	6.5a	17860_at	At4g27410
Protein phosphatase 2C	49	53	51	138	151	316	2.7	3.0	6.2a	18936_at	At1g72770
Protein phosphatase 2C	114	76	95	244	342	586	2.6	3.6	6.2	19638_at	At3g11410
Unknown	347	286	317	1,704	1,627	1,794	5.4	5.1	5.7	13645_at	At1g05340
G-box binding bZIP transcription factor	24	24	24	65	71	120	2.7	3.0	5.0	15214_s_at	At2g48270
Unknown	573	591	582	2,790	2,671	2,709	4.8	4.6	4.7ac	13225_s_at	At1g20440
DNA-binding myb-like protein, putative	78	92	85	205	224	384	2.4	2.6	4.5	15871_s_at	At3g24310
Zinc finger protein, putative	27	26	27	66	54	114	2.5	2.0	4.3	15356_at	At4g23450
Transcriptional activator, CBF1-like	132	82	107	3,239	275	405	30.3	2.6	3.8	17520_s_at	At4g25480
Receptor-like kinase, RLK3	62	45	54	167	129	196	3.1	2.4	3.7	20144_at	At4g25390
Dehydrin Xero2	639	424	532	3,514	1,648	1,835	6.6	3.1	3.5	19186_s_at	At3g50970
Unknown	731	586	659	4,214	1,923	2,183	6.4	2.9	3.3a	15103_s_at	At1g20450
Unknown	304	449	377	864	1,065	1,226	2.3	2.8	3.3	17384_at	At4g23630
Putative β-galactosidase	24	24	24	180	185	76	7.5	7.7	3.2	19008_s_at	At2g28470
Nodulin-like	55	61	58	422	161	179	7.3	2.8	3.1	13474_at	At2g40900
Unknown	31	28	30	102	85	89	3.5	2.9	3.0	19368_at	At1g27200
Protein kinase	80	67	74	206	180	213	2.8	2.4	2.9	18122_at	At2g30360
CCAAT-box-transcription factor, putative	24	24	24	116	87	66	4.8	3.6	2.8	20437_at	At5g47640
Protein kinase	26	28	27	78	70	66	2.9	2.6	2.4	17752_at	At2g32800
Histone H1	55	76	66	198	132	140	3.0	2.0	2.1	15695_s_at	At2g18050
Glucosyltransferase, putative	75	46	61	26	27	28	0.43	0.45	0.46	18471_at	At2g31790
Unknown	421	223	322	93	101	148	0.29	0.31	0.46	19398_at	At4g37540
Glc-6-phosphate 1-dehydrogenase	276	104	190	47	73	81	0.25	0.38	0.43	19424_at	At1g24280
Terminal flower (TFL1)	99	86	93	32	30	39	0.35	0.32	0.42	17029_s_at	At5g03840
Unknown	65	49	57	26	27	24	0.46	0.47	0.42	18833_at	At2g03260
Transcription factor ATMYB4	71	46	59	24	28	24	0.41	0.48	0.41	16534_s_at	At5g26660
Receptor-like protein kinase	98	24	61	24	24	24	0.39	0.39	0.39	16789_at	At1g05700
Auxin transport protein EIR1	296	362	329	124	138	126	0.38	0.42	0.38	12932_s_at	At5g57090
Unknown	1,394	536	965	381	267	364	0.39	0.28	0.38a	19216_at	At2g38310
Anthranilate N-benzoyltransferase-like	210	139	175	59	64	64	0.34	0.37	0.37	14705_i_at	At5g01210
Ribonuclease, putative	296	158	227	108	97	83	0.48	0.43	0.37	19815_at	At1g14210
Asp kinase-homoserine dehydrogenase	102	42	72	34	24	26	0.47	0.33	0.36	19749_at	At1g31230
High-affinity nitrate transporter NRT2	256	24	140	24	44	50	0.17	0.31	0.36	16615_s_at	At1g08090
Receptor-like protein kinase	105	35	70	31	26	24	0.44	0.37	0.34	20219_at	At2g28970
Ca2+-ATPase, AtACA4	219	117	168	76	62	55	0.45	0.37	0.33	18296_at	At2g41560
Fe(II)/ascorbate oxidase	123	24	74	24	24	24	0.33	0.33	0.33	14049_at	At4g25310
Unknown	532	164	348	139	109	103	0.40	0.31	0.30	20636_at	At4g17870
Receptor-like protein kinase	201	50	126	57	62	34	0.45	0.49	0.27	12276_at	At2g28960
MYB28-like transcription factor	122	59	91	29	24	24	0.32	0.27	0.27d	17975_at	At5g61420
1-aminocyclopropane-1-carboxylate oxidase	184	106	145	51	66	31	0.35	0.46	0.21	14039_at	At2g19590
Ferulate-5-hydroxylase (FAH1)	299	105	202	75	73	42	0.37	0.38	0.21	17089_s_at	At4g36220
Peroxidase ATP19a	354	466	410	111	63	82	0.27	0.15	0.20	13610_s_at	At4g11290
Member of lipase/acylhydrolase family	1,177	1,144	1,161	505	541	201	0.44	0.47	0.17	12779_f_at	At1g54000
Receptor-like protein kinase (IRK1)	480	167	324	148	107	56	0.46	0.33	0.17a	16818_s_at	At4g21410
Unknown	581	451	516	255	80	87	0.49	0.16	0.17	12791_r_at	At2g45180
Unknown	270	90	180	77	24	24	0.43	0.13	0.13e	18235_at	At1g27020
Peroxidase, putative	140	237	189	30	30	24	0.16	0.16	0.13	19602_at	At1g49570
Unknown	175	220	198	42	31	24	0.21	0.16	0.12	17440_i_at	At1g78860
Peroxidase ATP12a	791	748	770	297	210	91	0.39	0.27	0.12	17932_s_at	At1g05250
Member of lipase/acylhydrolase family	584	874	729	276	272	72	0.38	0.37	0.10	16493_at	At1g54010
Unknown	879	320	600	267	24	24	0.45	0.04	0.04e	20698_s_at	At2g40330
Peroxidase	1,535	636	1,086	39	66	24	0.04	0.06	0.02	12400_at	At5g19890

^a Shared response in leaves for 12 genes. 

^b Similar results with probe set #18700_r_at and 18699_i_at. 

^c Similar results with probe set #15997_s_at. 

^d Similar results with probe set #18742_f_at. 

^e Only examples where > 2-fold change persists at 27 h. 

Table V.

Overlap in root and leaves at 3 and 27 h for cold stress

Annotation	Expression Levels in Control						Fold Change, 4°C				Probe Set No.	AGI No.
	Roots			Leaves			Roots		Leaves
	3 h	27 h	Avg	3 h	27 h	Avg	3 h	27 h	3 h	27 h
Light-induced protein	52	24	38	24	24	24	10.2	38.8	75.5	231.8	16637_s_at	At4g14690
Dehydrin Xero2	639	424	531	24	24	24	6.6	9.7	14.5	187.6	19186_s_at	At3g50970
Cold-regulated protein cor15b	24	24	24	24	24	24	3.3	77.8	36.3	114.6	13785_at	At2g42530
UDP-rhamnosyltransferase	59	41	50	27	24	25.5	3.0	20.8	4.8	32.2	14984_s_at	At4g27570
Flavanone 3-hydroxylase (FH3)	82	127	104	62	50	56	4.0	14.8	10.8	31.0	18907_s_at	At3g51240
Putative β-amylase	24	24	24	141	172	156.5	21.8	65.7	8.1	25.0	18670_g_at	At4g17090
Myosin heavy chain-B	31	25	28	64	47	55.5	9.0	37.0	5.4	24.4	15083_at	At4g32190
NBD-like protein	101	113	107	43	33	38	3.5	7.8	12.5	24.2	16636_s_at	At5g44110
Unknown	34	24	29	24	25	24.5	4.9	15.6	3.5	20.4	16688_at	At1g10080
Unknown	24	51	37	24	24	24	7.7	14.0	8.3	18.7	18272_at	At2g40080
AP2 domain protein RAP2.1	60	39	49	30	26	28	4.6	13.4	2.3	12.7	20471_at	At5g67190
CONSTANS-like B-box zinc finger	29	24	26	100	63	81.5	6.2	13.2	5.7	12.4	20525_at	At2g31380
Unknown	51	31	41	26	24	25	7.7	11.1	7.3	10.0	14785_g_at	At2g46790
Squalene epoxidase-like	24	24	24	180	84	132	2.8	8.5	4.7	8.6	18484_at	At4g37760
Thaumatin-like protein	51	24	37	77	57	67	5.9	26.1	2.7	8.6	20384_at	At4g36010
Similar to prenyltransferase	24	24	24	69	52	60.5	3.0	4.2	5.7	7.9	18835_at	At1g78510
Unknown	24	24	24	24	24	24	5.0	19.5	2.3	7.0	15878_at	At4g33980
Unknown	279	353	316	208	218	213	2.8	3.3	3.8	7.0	19411_at	At2g37970
MYB transcription factor (CCA1)	26	29	27	160	103	131.5	18.8	20.5	4.8	7.0	17019_s_at	At2g46830
Similar to transcription factor CCA1	24	24	24	132	113	122.5	25.3	12.3	8.5	5.9	19866_at	At1g01060
CONSTANS-like	24	24	24	126	203	164.5	3.1	5.3	3.5	5.7	20299_at	At5g15850
Unknown	66	45	55	24	50	37	2.7	4.1	3.1	4.5	14923_at	At2g28320
AP2 domain transcription factor	44	65	54	33	42	37.5	2.7	7.6	3.0	4.3	15511_s_at	At2g28550
RING-H2 finger protein RHA3b	111	104	107	57	40	48.5	3.1	2.9	2.5	3.7	17047_s_at	At4g35480
Unknown	24	24	24	204	83	143.5	3.8	5.7	3.2	3.1	14432_at	At4g27030
H-protein promoter binding factor	152	123	137	79	97	88	5.3	3.3	5.1	3.1	16555_s_at	At3g47500
Similar to NorM in Vibrio parahaemolyticus	157	124	140	181	235	208	2.2	2.7	2.1	3.0	13025_at	At4g25640
Gly-rich protein	96	103	99	30	30	30	5.2	2.4	5.9	3.0	15115_f_at	At2g05380
Putative zinc-finger protein	49	59	54	122	120	121	8.8	11.8	2.2	2.7	20044_at	At4g27310
Unknown	40	30	35	24	24	24	3.0	5.3	3.4	2.6	18778_at	At4g15430
Gln-dependent Asn synthetase	39	52	45	185	109	147	3.2	11.6	3.2	2.2	15154_s_at	At3g47340
Lipase/acylhydrolase	1,177	1,144	1,161	175	105	140	0.44	0.37	0.49	0.41	12779_f_at	At1g54000
Unknown	173	85	129	68	79	73.5	0.43	0.28	0.46	0.33	15485_at	At2g27310
Calnexin-like	1,302	864	1,083	982	1,037	1,010	0.48	0.39	0.46	0.29	17473_at	At5g61790
Similar to stromal factor 2 in Mus musculus	409	253	331	282	271	276.5	0.39	0.14	0.47	0.29	14078_at	At2g25110
Similar to merozoite surface protein	104	124	114	170	132	151	0.41	0.21	0.46	0.27	12846_s_at	At3g43160
Ethylene-response element-binding protein	254	90	172	129	50	89.5	0.26	0.14	0.27	0.27	20489_at	At2g44840
Sugar transporter-like protein	73	59	66	322	192	257	0.41	0.36	0.46	0.24	17207_at	At4g36670
Unknown	59	56	57	113	99	106	0.47	0.42	0.43	0.23	17387_s_at	At2g03350
Calreticulin (crt1)	1,083	1,083	1,083	860	1,108	984	0.46	0.31	0.41	0.20	15654_s_at	At1g56340
Putative storage protein	615	764	689	270	235	252.5	0.48	0.11	0.31	0.10	15522_i_at	At4g24360
Ethylene-responsive element-binding factor 1	919	556	737	648	548	598	0.30	0.08	0.38	0.04	12904_s_at	At4g17500

Acute Responses Shared by All Three Stresses

Tables II and III together list 118 genes that are up- or down-regulated by all three stresses during the acute phase (first 3 h) of each stress response. These tables are arranged in descending order of -fold change observed in NaCl stress. Of the 118 genes that show changes, the largest category (29%) was annotated as “unknown,” 15% were predicted to be directly involved in regulating gene expression (e.g. transcription factors), 9% in membrane transport, and 8% in phosphoregulation. The 12 genes that were coregulated in both roots and leaves are identified in Table II. Among all of the shared 3 h responses, the transcript for LOW TEMPERATURE-INDUCED PROTEIN 78 (LTI/COR78, At5g52310) was observed as the most strongly induced (i.e. 98-fold with cold; 57-fold with NaCl). The actual level of induction was probably even greater, because the transcript was undetectable in controls (i.e. assigned a value of 24, which means that the signal was below the threshold for accurate detection).

Table III.

Overlap at 3 h in leaves for cold, mannitol, and NaCl stress

Annotation	Expression Levels						Fold Change at 3 h			Probe Set No.	AGI No.
	Control			3 h			4°C	Mannitol	NaCl
	3 h	27 h	Avg	4°C	Mannitol	NaCl
Low-temperature-induced protein 78	24	24	24	960	230	213	40.0	9.6	8.9a	15611_s_at	At5g52310
Δ-1-pyrroline 5-carboxylase synthetase	191	97	144	629	1,612	1,229	4.4	11.2	8.5a	14733_s_at	At2g39800
Putative calcium-binding EF-hand protein	48	24	36	153	294	293	4.3	8.2	8.1a	15052_at	At2g33380
Cold-regulated protein COR6.6 (KIN2)	157	60	108	1,784	1,402	805	16.4	12.9	7.4ab	18701_s_at	At5g15970
CCAAT-box-binding transcription factor	24	24	24	93	298	176	3.9	12.4	7.3	20437_at	At5g47640
Cold- and ABA-inducible protein kin1	151	82	116	1,662	1,366	817	14.3	11.7	7.0a	16474_s_at	At5g15960
Contains similarity to zinc-binding protein (PWA33)	24	24	24	290	257	130	12.1	10.7	5.4	14367_at	At1g60190
Unknown	334	145	239	2,268	2,146	1,275	9.5	9.0	5.3ac	15997_s_at	At1g20440
Unknown	24	24	24	81	144	121	3.4	6.0	5.0	15018_at	At1g79520
Myo-inositol 1-phosphate synthase	24	24	24	89	177	120	3.7	7.4	5.0	15621_f_at	At2g22240
Physical impedance induced protein	25	24	24	429	207	119	17.5	8.4	4.9	13004_at	At2g17840
bZIP transcription factor-like protein	24	29	26	56	133	108	2.1	5.0	4.1	13965_s_at	At4g34000
Homeobox-Leu zipper protein ATHB-12	24	33	28	89	285	107	3.1	10.0	3.8	16115_s_at	At3g61890
Neoxanthin cleavage enzyme-like protein	80	39	59	164	260	222	2.8	4.4	3.7	15761_at	At4g19170
Nitrate transporter, putative	161	131	146	438	428	530	3.0	2.9	3.6	19656_s_at	At2g28690
Remorin, non-specific DNA binding	75	164	119	483	541	432	4.0	4.5	3.6	18629_s_at	At2g45820
Unknown	47	56	51	107	280	169	2.1	5.4	3.3	20042_s_at	At4g34010
Aquaporin (PIP2B)	340	313	326	719	1,208	1,068	2.2	3.7	3.3	12769_at	At2g37170
Cold acclimation protein	372	279	325	872	992	1,058	2.7	3.0	3.3	12749_at	At2g15970
Ammonium transporter ATM1,2	152	60	106	574	442	339	5.4	4.2	3.2d	16561_s_at	At1g64780
Putative β-glucosidase	44	266	155	528	515	484	3.4	3.3	3.1	18314_i_at	At4g27830
Protein phosphatase 2C ABI2 (PP2C)	26	24	25	68	101	78	2.7	4.0	3.1	17929_s_at	At5g57050
Unknown	74	42	58	207	224	178	3.6	3.9	3.1	19982_at	At1g79270
Unknown	38	28	33	209	90	100	6.3	2.7	3.0	18289_at	At2g24540
Transcriptional activator CBF1	43	24	33	307	93	98	9.2	2.8	2.9	16111_f_at	At4g25490
Potassium channel protein AKT3	28	24	26	66	69	75	2.5	2.7	2.9	16163_s_at	At4g22200
Nap gene	139	132	135	308	368	386	2.3	2.7	2.8	17880_at	At4g27410
Unknown	299	309	304	1,444	1,216	856	4.8	4.0	2.8	18594_at	At1g01470
Sugar transport protein, ERD6	24	24	24	61	57	67	2.5	2.4	2.8	12698_at	At1g08920
Sulfate transporter ATST1	24	24	24	68	53	65	2.8	2.2	2.7	17041_s_at	At3g51900
Senescence-associated protein sen1	222	146	184	534	596	488	2.9	3.2	2.7	15098_s_at	At4g35770
Unknown	439	464	451	2,355	1,894	1,171	5.2	4.2	2.6	15103_s_at	At1g20450
Suc transport protein, SUC2	78	70	74	156	181	191	2.1	2.4	2.6	13099_s_at	At1g22710
Protein phosphatase 2C (AtP2C-HA)	92	74	83	320	268	207	3.9	3.2	2.5	18936_at	At1g72770
Gln-dependent Asn synthetase	185	109	147	472	417	355	3.2	2.8	2.4	15154_s_at	At3g47340
Nitrate transporter	210	106	158	469	360	364	3.0	2.3	2.3	12457_at	At3g21670
Unknown	57	42	49	128	125	114	2.6	2.5	2.3	14582_at	At2g38800
Unknown	55	43	49	162	330	112	3.3	6.7	2.3a	13645_at	At1g05340
PMP31 protein	57	45	51	206	125	114	4.0	2.5	2.2	16322_at	At3g47430
Calnexin-like protein	982	1,037	1,010	468	450	483	0.46	0.45	0.48	17473_at	At5g61790
Unknown	84	42	63	28	30	30	0.44	0.48	0.48	14381_at	At2g02810
Putative phi-1-like phosphate-induced	765	853	809	77	101	379	0.10	0.12	0.47	14077_at	At4g08950
RNA helicase-like protein	59	57	58	24	24	27	0.41	0.41	0.47	18016_r_at	At5g08610
Class 2 non-symbiotic hemoglobin	273	199	236	93	91	106	0.39	0.39	0.45	12430_at	At3g10520
Putative cytochrome P450	77	62	69	24	24	31	0.35	0.35	0.45	19288_at	At2g27690
Unknown	52	62	57	24	24	25	0.42	0.42	0.44	14998_at	At2g30590
DEAD box RNA helicase (RH22)	75	72	73	31	30	32	0.42	0.41	0.44	15906_s_at	At1g59990
Unknown	87	24	55	25	24	24	0.45	0.43	0.43	19577_at	At1g65390
Unknown	146	115	130	48	39	56	0.37	0.30	0.43	15403_s_at	At2g31730
Putative protein endosperm specific protein	127	167	147	30	24	55	0.20	0.16	0.37	18265_at	At4g12730
Unknown	2	671	676	154	126	251	0.23	0.19	0.37	19216_at	At2g38310
Extensin-like Pro-rich protein	551	887	719	138	101	266	0.19	0.14	0.37	12115_at	At4g22470
Putative pollen-specific protein	206	268	237	71	34	87	0.30	0.14	0.37	19487_at	At4g12420
Unknown	148	240	194	74	54	71	0.38	0.28	0.37	18564_at	At2g34300
Ribosomal protein S11-like	81	73	67	24	24	24	0.36	0.38	0.36	17425_s_at	At4g30800
ACC synthase	191	141	166	37	31	57	0.22	0.19	0.34	18296_at	At4g26200
Unknown	70	84	77	24	24	26	0.31	0.31	0.34	20015_at	At1g10020
Mitochondrial chaperonin (HSP60)	88	159	123	38	24	39	0.31	0.19	0.32	19430_at	At2g33210
Putative isp4 protein	104	112	108	32	24	34	0.30	0.22	0.31	20089_at	At4g27730
Probable arabinogalactan protein	935	871	903	136	86	263	0.15	0.10	0.29	14947_at	At4g37450
Pectinesterase	276	364	320	65	104	93	0.20	0.33	0.29e	19267_s_at	At4g02330
Unknown	78	88	83	24	24	24	0.29	0.29	0.29	15859_at	At2g28570
Peroxidase ATP24a	216	272	244	39	41	67	0.16	0.17	0.27	18946_at	At5g39580
Xyloglucan endo-1,4-β-d-glucanase (XTR-6)	346	613	479	55	29	79	0.11	0.06	0.16	17533_s_at	At4g25810
Receptor-like protein kinase	174	170	172	43	29	28	0.26	0.17	0.16a	16818_s_at	At4g21410

^a Only examples where >2-fold change persists at 27 h. 

^b Similar results with probe set #18699_i_at and 18700_r_at. 

^c Similar results with probe set #13225_s_at. 

^d Similar results with probe set #17572_s_at. 

^e Similar results with 14612_at. 

NaCl-Specific Responses

Table IV (Supplemental Table 2E, which can be viewed at www.plantphysiol.org) contains 22 genes that are exclusively regulated by salt stress at both 3 and 27 h. This represents only 5% of the combined salt-specific changes observed at 3 and 27 h in the root. Although most of the remaining 440 changes are likely to represent salt-specific changes, these changes were only observed once as part of a transient response and were therefore not listed in a stress-specific response table. Of the 22 salt-specific genes persisting as a 3- and 27-h response, the largest category (50%) was related to oxidative stress enzymes (e.g. glutathione reductase and cytochrome P450), 23% were annotated as “unknown,” and only one gene each was predicted to be directly involved in regulating gene expression, membrane transport, or phosphoregulation. The greatest -fold induction was observed for a putative “steroid sulfotransferase” At2g03760 (19-fold at 3 h). Of all salt-induced changes (shared or specific), this putative steroid sulfotransferase ranked as the fourth highest -fold change.

Table IV.

Overlap at 3 and 27 h in root for NaCl stress

Annotation	Expression Levels									Fold Change						Probe Set No.	AGI No.
	Control			4°C		Mannitol		NaCl		4°C		Mannitol		NaCl
	3 h	27 h	Avg	3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h
Steroid sulfotransferase,  putative	24	33	28.5	26	149	34	24	551	129	0.9	5.2	1.2	0.8	19.3	4.5a	17073_s_at	At2g03760
β-glucosidase-like protein	29	117	73	61	325	152	69	306	237	0.8	4.5	2.1	0.9	4.2	3.2	12574_at	At3g60140
Cytochrome P450-like  protein	24	24	24	24	24	32	24	279	75	1.0	1.0	1.3	1.0	11.6	3.1	14032_at	At4g37370
Hexokinase (ATHXK2)	30	34	32	27	64	50	66	92	82	0.8	2.0	1.6	2.1	2.9	2.6	15175_s_at	At2g19860
Alternative oxidase 1a  precursor	277	201	239	219	596	448	216	3,131	606	0.9	2.5	1.9	0.9	13.1	2.5	15582_s_at	At3g22370
Glutathione reductase,  cytosolic	291	465	378	675	789	496	517	779	928	1.8	2.1	1.3	1.4	2.1	2.5	16159_s_at	At3g24170
Cytochrome P450  monooxygenase	33	54	43.5	54	35	59	75	100	99	1.2	0.8	1.4	1.7	2.3	2.3	17039_s_at	At3g26220
Unknown	33	44	38.5	24	24	59	27	101	86	0.6	0.6	1.5	0.7	2.6	2.2	19873_at	At2g41810
Putative transcriptional  repressor	73	53	63	65	556	69	48	438	130	1.0	8.8	1.1	0.8	7.0	2.1	12951_at	At1g10170
1,4-hydroxyphenylpyruvate  dioxygenase	56	101	78.5	147	264	179	83	526	160	1.9	3.4	2.3	1.1	6.7	2.0	15689_s_at	At1g06570
Unknown	122	123	123	139	47	79	103	55	59	1.13	0.38	0.64	0.84	0.45	0.48	18881_at	At1g12080
Glycogenin, putative	423	71	247	433	240	134	208	112	118	1.75	0.97	0.54	0.84	0.45	0.48	16712_at	At2g35710
Auxin-induced protein,  putative	181	108	145	83	131	73	85	54	68	0.57	0.91	0.51	0.59	0.37	0.47	17869_at	At1g60680
Unknown	83	58	70.5	49	24	63	83	24	33	0.70	0.34	0.89	1.18	0.34	0.47	14691_at	At3g22240
Unknown	203	243	223	204	153	206	220	97	104	0.91	0.69	0.92	0.99	0.43	0.47	18279_s_at	At2g37490
Putative ACC oxidase	577	642	610	458	499	297	367	273	262	0.75	0.82	0.49	0.60	0.45	0.43	18310_at	At1g12010
pEARLI 1-like protein	777	936	857	1,099	885	505	769	338	365	1.28	1.03	0.59	0.90	0.39	0.43	18983_s_at	At4g12510
Putative reticuline oxidase-like protein	182	175	179	107	283	131	108	89	76	0.60	1.59	0.73	0.61	0.50	0.43	14267_at	At1g30760
Unknown	511	424	468	440	257	239	342	130	195	0.94	0.55	0.51	0.73	0.28	0.42	16438_at	At1g03870
Nodulin-26-like protein	92	53	72.5	81	28	24	46	24	24	1.12	0.39	0.33	0.63	0.33	0.33	19847_s_at	At4g19030
ExtA (embCAA47807.1)	431	484	458	878	764	274	443	109	145	1.92	1.67	0.60	0.97	0.24	0.32	16489_at	At5g46900
Peroxidase, putative	531	233	382	163	242	239	171	163	93	0.43	0.63	0.63	0.45	0.43	0.24	16971_s_at	At3g01190

^a Similar results with probe set #14843_s_at. 

Cold-Specific Responses

Table V (Supplemental Table 4, which can be viewed at www.plantphysiol.org) contains 42 genes that are exclusively regulated by cold stress in both root and leaves at both 3 and 27 h. This represents only 2% of all the cold-induced changes. This set of changes represents the most reliable set of changes in this study, being detected as specifically cold induced in four different samples, whereas no change was detected in the 12 other non-cold-stressed samples. Of these 42 genes, the largest two categories (approximately 20%) were annotated as unknown or predicted to be directly involved in regulating gene expression. Only one gene was annotated as a membrane transporter, and none was directly related to phosphoregulation. The greatest -fold induction was observed for an EARLY LIGHT-INDUCED PROTEIN (ELIP; At4g14690; 232-fold at 27 h in leaves).

Top Three Changes

Table VI shows the three highest ranking -fold inductions for each of the three individual stresses. This table revealed that the three largest -fold changes were all induced by cold stress. Interestingly, the LTI/COR78 gene ranked first in all three stress treatments.

Table VI.

Top three highest induced expression changes for 4°C, mannitol, and NaCl stresses

	Control, Avg		4°C				Mannitol
	Leaves	Roots	Leaves		Roots		Leaves		Roots
			3 h	27 h	3 h	27 h	3 h	27 h	3 h	27 h
Cold-1	24	24	40.0	225.3	98.0	252.3	9.6	6.3	38.6	2.0
Cold-2	24	38	75.5	231.8	10.2	38.8	4.1	1.4	1.2	0.7
Cold-3	24	24	36.3	114.6	3.3	77.8	1.5	1.0	1.0	1.0
Mannitol-1	24	24	40.0	225.3	98.0	252.3	9.6	6.3	38.8	2.0
Mannitol-2	108.5	584	16.4	75.8	4.8	14.8	12.9	5.1	6.7	1.5
Mannitol-3	24	24	3.9	1.0	4.8	2.4	12.4	6.0	3.6	1.0
NaCl-1	24	24	40.0	225.3	98.0	252.3	9.6	6.3	38.8	2.0
NaCl-2	26	24	2.0	5.8	2.5	4.0	8.9	2.1	7.4	1.1
NaCl-3	24	24	1.3	23.0	3.6	41.7	5.8	1.0	5.8	1.0

NaCl				Probe Set No.	AGI No.	Annotation
Leaves		Roots
3 h	27 h	3 h	27 h
8.9	2.8	58.5	1.5	15611_s_at	At5g52310	Low-temperature-induced protein 78
1.5	1.0	1.8	1.8	16637_s_at	At4g14690	Light induced protein
1.0	1.0	1.0	1.0	13785_at	At2g42530	Cold-regulated protein cor15b
8.9	2.8	58.5	1.5	15611_s_at	At5g52310	Low-temperature-induced protein 78
7.4	2.2	7.3	1.6	18701_s_at	At5g15970	Cold-regulated protein COR6.6 (KIN2)
7.3	1.0	2.8	1.0	20437_at	At5g47640	Putative CCAAT-box transcription factor
8.9	2.8	58.5	1.5	15611_s_at	At5g52310	Low-temperature-induced protein 78
2.8	1.3	28.4	1.3	14097_at	At2g47770	Unknown
1.5	1.0	27.9	1.0	19152_at	At5g06760	Late embryogenesis abundant protein

DISCUSSION

The large number of stress-regulated transcriptome changes observed here underscores the difficulty of understanding the global context of a stress response. Using probe sets representing approximately 8,100 unique Arabidopsis genes, our expression profiling revealed a greater than 2-fold change for 2,409 genes in response to cold, salt, or osmotic stress (Supplemental Table 1, which can be viewed at www.plantphysiol.org). Extrapolating to the entire Arabidopsis transcriptome, the expression levels of more than 7,000 genes (approximately 30% of the genome) are potentially regulated by these common abiotic stresses.

Because all aspects of plant physiology are impacted by stress, we consider a large number of transcriptome changes to be reasonable. Although many stress-regulated genes have been identified previously (http://stress-genomics.org), our study provides the first global expression profile, to our knowledge, comparing three of the major abiotic stresses: salt, hyperosmotic, and cold. Our greatly expanded list of potential stress-regulated genes is consistent with our use of a GeneChip microarray strategy that allowed a sensitive and accurate quantification of a large number probe sets. With the observation of 2,409 stress-regulated changes, it is impractical to discuss the potential functions of individual changes. Instead we offer selected comments and observations to illustrate important themes.

The GeneChip Can Reliably Detect 2-Fold Changes

We expect that most of the 2,409 changes represent a biological response of the plant to its environment rather than a technical artifact of inconsistent hybridizations or probe labeling. A false change error of less than 0.25% changes is expected (i.e. around six genes) from control experiments conducted under identical conditions with the same detection threshold (i.e. expression levels >25; Zhu and Wang, 2000). To minimize the detection of random changes from a single sample, the GeneChip was probed with RNA pooled from two independent experiments. Although some of the observed changes may still be random or functionally unrelated to a stress treatment, our results did confirm many of the stress-regulated genes found in other surveys conducted on a smaller scale. For example, we detected all of the cold-regulated changes identified by Seki et al. (2001) from their analysis of 1,300 genes. From the set of 85 salt-regulated transcripts identified by Gong et al. (2001), 28 were represented by probe sets on the GeneChip microarray, of which more than 50% were observed to be stress regulated in this study. The incomplete overlap with salt-regulated genes observed by Gong et al. may be attributable to differences in growth conditions or detection methodologies.

Interpreting Transcriptome Changes Requires Caution

When considering the relative significance for each of the 2,409 changes, two important qualifications must be considered. First, expression profiling does not by itself define the critical genes required for any of stress responses. It is important to emphasize that changes in mRNA levels may not correlate with changes in protein or enzyme activity levels (e.g. Gygi et al., 1999). Nevertheless, expression profiles do provide useful starting points for more in depth analyses (e.g. Harmer et al., 2000). For instance, expression profiling can be used to create a candidate gene list to help prioritize the arduous task of using reverse genetics to assign functionality to genes. In the present study, stress-induced transcription factors represent good candidates for under/overexpression experiments.

Second, any interpretation of our results must include the realization that a plant is always changing and adapting to its environment. Thus, experimental changes are always being observed in a background of uncertain variation. Some of the changes observed here may be unique to our experimental conditions. We note two potentially important variables. First, tissue was harvested 3 h into the photoperiod. A 24-h interval was maintained between the two time points to avoid mistaking a circadian clock-controlled change for a stress-induced change. Nevertheless, some stress responses may be very different if observed in the dark versus the light. Second, all plants were stressed after exposure to fresh medium. Although the addition of fresh medium allowed a uniform and rapid initiation of parallel stress treatments, the fresh medium also induced a number of changes on its own. Thus, our experimental design certainly resulted in both hiding and revealing stress-induced changes. For example, fresh medium appeared to induce a greater than 10-fold increase in the expression levels of a nitrate transporter gene NRT2 (At1g08090) in the roots (Supplemental Table 2A, can be viewed at www.plantphysiol.org). However, this induction was almost completely blocked by all three stresses and therefore showed up as a common stress-induced change. This example emphasizes that the physiological status of the plant will impact how it responds to stress. Because plants are constantly adapting to a changing environment, there is no perfect “background” condition to reliably identify all stress-specific changes. In the future, additional expression profiling will be needed to classify stress-induced changes under different experimental conditions.

To provide a starting point for considering the importance of a given stress-induced change, we organized a set of tables to reveal the most consistent set of stimulus-specific or shared responses (Fig. 2; Tables II–VI; Supplemental Tables 2 and 3, which can be viewed at www.plantphysiol.org). We decided to only list genes that passed the more conservative criteria for reproducibility at different time points, tissues, or treatments. We did not include changes observed only once. However, these criteria for “reproducibility” excluded more than 1,000 potentially important changes that were only observed in a transient and stress-specific fashion.

Cold, NaCl, and Mannitol Trigger Primarily Stimulus-Specific Responses

Our results indicate that the majority of transcriptome changes are stimulus specific and not part of a general stress response common to cold, osmotic, and NaCl stress. During the acute phase of the stress responses (3 h), less than 5% of the changes were shared by all three stresses. By 27 h, the shared responses were reduced to less than 0.5%. This picture of predominately stress-specific responses is analogous to that observed in a comparison of drought- and NaCl-stressed barley, as revealed by an expression profile of 1,463 genes (Ozturk et al., 2002). Nevertheless, our results are in contrast to the observation made by Seki et al. (2001) from their expression profile analysis of 1,300 Arabidopsis genes. In their study, the majority of drought and cold stress-regulated changes appeared to be part of a shared response. A partial explanation for this difference may lie with the increased sensitivity of the GeneChip compared with the cDNA spotting technology used by Seki et al. (2001). Our GeneChip analysis allowed us to compare more genes, detect lower abundance mRNAs, and more accurately score changes close to a 2-fold threshold. Thus, although our analysis identified even more shared responses than previous studies (e.g. 142 from this study compared with 16 by Seki et al. [2001]), these shared responses only represented a minor fraction of the observable changes.

NaCl and Mannitol Induced Both Iso-Osmotic- and Stress-Specific Responses

We used a 200 mm mannitol treatment as an iso-osmotic control for the 100 mm NaCl stress. Not surprisingly, 174 shared “osmotic stress”-specific changes were observed at the 3-h post-stress time point. Nevertheless, the majority of NaCl or mannitol changes appeared to be stimulus specific. Thus, these two osmotic stress treatments clearly triggered very different responses within the first 3 h of stress.

Interestingly, about 40% (68) of the common 3-h iso-osmotic changes were observed in leaves. This is of special interest because the leaves were not in direct contact with the 100 mm NaCl or the 200 mm mannitol medium. These relatively rapid changes provide candidate markers for detecting the long-distance messengers that move from the root to the shoot. Potential long-distance signals include nutrients, hormones such as abscisic acid (ABA), or calcium-mediated action potentials (Dennison and Spalding, 2000; Forde, 2002; Knight, 2000; Schroeder et al., 2001) or a disturbed water potential gradient from roots to leaves (Nonami et al., 1997). However, our experiments were not conducted to exclude the possibility that, within 3 h, NaCl and mannitol had a direct effect on leaf tissues by translocation through the vascular system.

An important design feature of this study was the ability to compare multiple stresses and time points to more precisely identify potential stimulus-specific responses. For example, we identified 27 NaCl-specific responses (Table IV; Supplemental Tables 2E and 3E, which can be viewed at www.plantphysiol.org) and 46 mannitol-specific changes (Supplemental Tables 2F and 3F, which can be viewed at www.plantphysiol.org) that occurred at both 3 and 27 h. Of these, 16 were annotated as unknown genes. In these lists, the most highly induced genes for NaCl and mannitol stress, respectively, were a putative steroid sulfotransferase (At2g03760; 19-fold with NaCl), and a putative transcription factor (At5g47640; 12-fold with mannitol).

Numerous Cold-Specific Changes

Of the three stress treatments used here, cold induced nearly twice as many changes as either mannitol or NaCl (2,086 in total; Fig. 1). In the roots and leaves respectively, 173 and 188 cold-specific changes were observed as reproducible changes between 3 and 27 h (Supplemental Tables 2G and 3G, which can be viewed at www.plantphysiol.org), compared with 73 changes combined for NaCl and mannitol (Supplemental Tables 2E and F, 3E and F, which can be viewed at www.plantphysiol.org).

As mentioned above, an important design feature of this study was the ability to compare multiple stresses and time points to more precisely identify potential stimulus-specific responses. In the case of cold stress (Supplemental Tables 2G and 3G, which can be viewed at www.plantphysiol.org), we further explored the overlapping responses between root and leaves at 3 and 27 h to identify the most reliable set of mRNAs that are regulated specifically by cold, regardless of tissue or time. Forty-two genes were identified in this comparison (Table V, shown here), of which 10 were annotated as unknown. In this list, the most highly induced genes in leaves and roots respectively were ELIP (At4g14690; 231-fold induced) and COLD-REGULATED PROTEIN 15B (COR15B; At2g42530; 78-fold induced). Abiotic stress regulation of ELIP gene expression has been observed previously (Adamska and Kloppstech, 1994; Ouvrard et al., 1996; Shimosaka et al., 1999). Biochemical data indicate that ELIPs bind chlorophyll a and lutein (Adamska et al., 1999), but an exact role for their function in the plant's response to abiotic stress has not been reported.

Overlapping Responses to Salt, Osmotic, and Cold Stress

Although many stress-regulated genes have been identified previously, another important design feature of this study was the ability to compare multiple stresses at different time points to more precisely identify changes that are part of a “common” or “shared” response. At 3 h, we observed a total of 118 unique gene changes shared by all three stresses (Tables II and III). Of these, 30 (25%) were annotated as unknown. This group of stress-regulated genes is of potential interest in identifying targets of common stress-signaling pathways.

Most shared responses were specific for either roots or leaves, because only 12 of 118 showed coregulation in both tissues (Table II). In this list, LTI/COR78 (Atg52310) was the most highly induced in both leaves and roots (respectively, 40- and 98-fold for cold; 9- and 57-fold for NaCl; and 10- and 39-fold for mannitol). The biochemical function of LTI/COR78 is poorly understood, as are most of the highly induced genes observed for all three stress (Table VI).

In the roots and leaves, respectively, only two and eight genes were consistently observed as part of the shared response at both time points (Supplemental Tables 2A and 3A; they can be viewed at www.plantphysiol.org). One-half of these 10 genes were annotated as unknown. Interestingly, the expression of LTI/COR78, which was the most highly induced gene for both tissues at 3 h, was only observed as a consistent change in the leaves (i.e. 3 and 27 h). In 27-h roots, LTI/COR78 transcript levels returned to near normal for NaCl and mannitol stress treatments while more than doubling expression levels under cold stress. This example shows how even the most dramatic overlapping stress responses could be missed by an experiment that examined a limited number of time points or ignored tissue-specific differences.

Dynamic Changes Occur between 3 and 27 h of Stress

There were dramatic changes in both the numbers and identities of transcriptome changes between the 3 and 27 h stress time points for each stress treatment. We offer three examples to illustrate this point. First, in the transition from 3 to 27 h, the total number of shared changes (all three stresses) underwent a 4-fold reduction from 118 to 24. This dramatic reduction is consistent with the plant switching from shared stress responses to more stress-specific responses.

Two additional examples can be illustrated by examining the stress-specific responses. In the cold stress response, between 3 and 27 h both leaf and root tissues responded with a greater than 4-fold increase in the number of changes (Fig. 2). Interestingly, the opposite trend (4-fold reduction) was seen with the NaCl stress. This may reflect the success of the plant in mounting a NaCl-resistance response and the restoration of the transcriptome to a prestress program, or alternatively, the failure of the plant to establish an adaptive response. Given that Arabidopsis is classified as a salt-sensitive plant, the latter interpretation is worth considering. In contrast, the continuing increase in number of cold stress changes suggests a fundamentally different stress response. In this case, “cold stress” transcriptome of the plant appears to be moving toward a new and dramatically different “steady state,” presumably better adapted to a cold environment.

The Root and Leaves Express Different Sets of Stress-Regulated Genes

Although roots and leaves contain different sets of specialized cells, it was not known to what extent the stress response programs would differ between these tissues. Our results support the hypothesis that roots and leaves have very different transcriptome responses to all three stresses. For example, 86% of the cold-induced changes are not shared between root and leaves (Fig. 2; Table V). Although similar root-leaf differences were also observed with NaCl and mannitol stress, these differences may partly reflect the fact that only the roots (and not leaves) were in direct contact with NaCl and mannitol treatments.

68% of the Circadian Controlled Genes Are Linked to Stress Regulation

Our results support a hypothesis that many of the circadian clock-controlled genes are also subject to stress regulation (Harmer et al., 2000). One important function of the circadian clock may be to regulate gene expression in “anticipation” of a predictable stress. For example, because the peak time for cold stress is normally predawn, a plant's ability to pre-activate a cold stress pathway may provide a higher level of resistance. Harmer et al. (2000) recently identified 18 known stress-regulated genes in an analysis of circadian controlled genes. Here, we identified 306 additional stress-regulated genes among the 453 known circadian controlled genes. Together our studies suggest that approximately 68% of the circadian controlled genes are linked to a stress response pathway, strengthening the argument that the circadian clock helps a plant adapt to daily environmental changes.

2,409 Steps toward Enhanced Annotation of the Genome

Our results revealed stress-regulated expression patterns of every conceivable pattern. For example, KIN2, which has been well characterized as part of the cold stress response (Kurkela and Borg-Franck, 1992), was also induced by NaCl and mannitol as part of an overlapping 3-h short-term response in both roots and leaves. However, after 27 h, roots and leaves displayed different patterns. In roots, the expression of KIN2 returned to normal for NaCl and mannitol stress, but remained high for cold stress (Supplemental Table 2G, which can be viewed at www.plantphysiol.org). In contrast, the expression of KIN2 in leaves remained high for all three stresses (Supplemental Table 3C, which can be viewed at www.plantphysiol.org). The variation in expression patterns emphasizes that each stress response examined in this study involves complex regulatory interactions.

Our study provides the first evidence for stress regulation of more than 370 genes with unknown functions. In addition, we extended the knowledge base for many already known stress-regulated genes, providing insights into their tissue specificity and regulation by multiple stresses. For example in leaves at 3 h post-stress, we observed an increase in transcript levels for protein phosphatase ABA Insensitive-2 and a transcriptional activator CBF1(At4g25490). These genes have been well studied in connection to stress responses (e.g. Leung et al., 1997; Jaglo-Ottosen et al., 1998; Sheen, 1998). Interestingly, ABA Insensitive-2 and CBF1 were not observed in roots as part of the 3-h acute response shared by all stresses. Instead, the shared response in roots included a different set of phosphatases and a related CBF1-like transcription factor. These examples illustrate two important points. First, the details of stress response may vary for different tissues and cell types. Second, some changes have the potential to make global changes in cellular functions, for example by altering phosphosignaling pathways or transcription.

The Role of Transcription and RNA Stability in Regulating the Transcriptome

Considerable effort has been made to identify stress-regulated promoter elements (Seki et al., 2001). One reason is to facilitate the engineering of plants with new or altered stress-regulated genes. The data set presented here was incorporated into a larger study of biotic and abiotic stress-regulated promoters (Chen et al., 2002). As expected, many of the cold-induced genes were found to have promoters with dehydration response element-like or ABA response element-like binding elements, providing the potential for regulation by DREB/CBF transcription factors and ABA. However, many of our 2,409 stress-regulated genes did not. This may reflect (a) the presence of undiscovered stress-regulated promoter elements, or (b) a large number of changes caused by differences in mRNA stability instead of gene transcription. More studies will be needed to understand the mechanisms by which the levels of each mRNA are regulated during stress responses.

The Role of Calcium Signals in Triggering General and Stress-Specific Responses

A central hypothesis supported by this study is that an abiotic stress initially triggers a set of common stress response pathways (e.g. output seen in Tables II and III) that are subsequently modified to be highly stimulus specific. Calcium signals have been observed as an early response to all three stresses used here (Knight, 2000). However, it is not clear whether these calcium signals are initiating a general stress response or communicating more specific information necessary to develop a stimulus-specific response. In addressing this question, one must consider that the same stress applied to different cell types can result in different calcium signatures (Kiegle et al., 2000). Thus, an important challenge for the future is to understand at the cellular level how cross-talk between calcium and other signal transduction pathways creates a stimulus-specific response.

MATERIALS AND METHODS

Stress Treatments and Sample Preparations

Seven-day-old axenic seedlings of Arabidopsis (Columbia) were transferred to rafts floating on hydroponic medium in Magenta boxes (Sigma-Aldrich, St. Louis) and grown for 3 weeks with gentle agitation. Light (75 microeinsteins; a mixture of cool-white fluorescent and incandescent) was provided on a 12-h/12-h light/dark cycle. Medium was provided as 0.5× Murashige and Skoog salts, 0.5 g L⁻¹ MES, 0.5× vitamins (Sigma-Aldrich), pH 5.7, and 0.5% (w/v) Suc. At the time of stress treatments, plants were still in a vegetative growth phase (i.e. pre-bolting). To initiate stress treatments, old medium were replaced with fresh medium that was prechilled to 4°C (cold stress) or supplemented with 100 mm NaCl (salt stress) or 200 mm mannitol (hyperosmotic stress). Cold stress was maintained for the duration of the experiment by placing Magenta boxes on ice. A fresh medium-only control was conducted in parallel. Stress treatments were initiated just after the lights came on, with samples taken at 3- and 27-h time points. Roots and leaves (entire shoot) were separated and frozen in liquid nitrogen. Each stress treatment and RNA extraction was replicated in two independent experiments. Total RNA was extracted from frozen and pulverized tissues using an RNeasy column (Qiagen USA, Valencia, CA). RNA samples for each replicate were pooled to obtain a single RNA sample for cDNA and cRNA probe preparation and expression profiling.

Expression Profiling

Detailed sample preparation and hybridization procedures were described previously (Zhu et al., 2001). Double-strand cDNAs were synthesized from 0.5 μg of total RNA using oligo(dT₍₂₄₎)primer containing 5′-T7 RNA polymerase promoter sequence SuperScript II (Invitrogen, Carlsbad, CA). Biotinylated complementary RNAs (cRNAs) were transcribed in vitro from synthesized cDNA by T7 RNA polymerase (ENZO Biochem, New York). Hybridizations with labeled cRNAs were conducted with Arabidopsis GeneChip Microarray (Affymetrix, Santa Clara, CA). This GeneChip contained probe sets for approximately 8,100 Arabidopsis genes (Zhu and Wang, 2000). Probe preparation (cRNA), hybridizations, and normalizations were conducted according to protocols optimized for sensitivity and reproducible comparisons (Harmer et al., 2000; Zhu and Wang, 2000). Expression data were normalized globally before data analysis. Genes with accurately detectable transcript levels were defined by probe sets showing averaged expression levels equal to or greater than 25, as described (Zhu and Wang, 2000). For probe sets showing weaker signals, expression values were adjusted up to 24 for further data comparisons. The -fold changes between stress treatments and fresh medium control were calculated by dividing stress-treated expression values by the averaged control expression values. The averaged control expression values were calculated by averaging the control value from the 3- and 27-h fresh medium samples. Using the above criteria for identifying genes displaying greater than 2-fold change, we expected less than 0.25% false changes resulting from inaccuracies of hybridization and detection.