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Molecular Plant Advance Access originally published online on January 29, 2008
Molecular Plant 2008 1(2):321-337; doi:10.1093/mp/ssm021
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© The Author 2008. Published by the Molecular Plant Shanghai Editorial Office in association with Oxford University Press on behalf of CSPP and IPPE, SIBS, CAS.

Comprehensive Transcriptome Analysis of Auxin Responses in Arabidopsis

Ivan A. Paponova,1,2, Martina Paponova,2, William Tealea, Margit Mengesb, Sohini Chakraborteeb, James A.H. Murrayb and Klaus Palmea,1

a Faculty of Biology, University of Freiburg, Schänzlestrasse 1, 79104 Freiburg, Germany
b Institute of Biotechnology, University of Cambridge, Cambridge CB2 1QT, United Kingdom

1 To whom correspondence should be addressed. E-mail klaus.palme{at}biologie.uni-freiburg.de. (K.P.); ivan.paponov{at}biologie.uni-freiburg.de (I.P.)


    Abstract
 TOP
 Abstract
 INTRODUCTION
 RESULTS AND DISCUSSION
 METHODS
 SUPPLEMENTARY DATA
 
In plants, the hormone auxin shapes gene expression to regulate growth and development. Despite the detailed characterization of auxin-inducible genes, a comprehensive overview of the temporal and spatial dynamics of auxin-regulated gene expression is lacking. Here, we analyze transcriptome data from many publicly available Arabidopsis profiling experiments and assess tissue-specific gene expression both in response to auxin concentration and exposure time and in relation to other plant growth regulators. Our analysis shows that the primary response to auxin over a wide range of auxin application conditions and in specific tissues comprises almost exclusively the up-regulation of genes and identifies the most robust auxin marker genes. Tissue-specific auxin responses correlate with differential expression of Aux/IAA genes and the subsequent regulation of context- and sequence-specific patterns of gene expression. Changes in transcript levels were consistent with a distinct sequence of conjugation, increased transport capacity and down-regulation of biosynthesis in the temperance of high cellular auxin concentrations. Our data show that auxin regulates genes associated with the biosynthesis, catabolism and signaling pathways of other phytohormones. We present a transcriptional overview of the auxin response. Specific interactions between auxin and other phytohormones are highlighted, particularly the regulation of their metabolism. Our analysis provides a roadmap for auxin-dependent processes that underpins the concept of an ‘auxin code’—a tissue-specific fingerprint of gene expression that initiates specific developmental processes.


    INTRODUCTION
 TOP
 Abstract
 INTRODUCTION
 RESULTS AND DISCUSSION
 METHODS
 SUPPLEMENTARY DATA
 
Auxin is a key regulator of plant development. It influences cell division, cell elongation and programmed cell death, driving embryonic and post-embryonic development (Davies, 2004). The effect of auxin is dependent on cell type: at the same concentration, indole-3-acetic acid (IAA) simultaneously stimulates hypocotyl elongation, suppresses main root growth, induces lateral root initiation, and stimulates root hair formation. An intricate network of interactions underlies this complexity and is under both transcriptional and post-translational control (Theologis and Ray, 1982; Gray et al., 2001). The fulcrum of auxin signaling is the interaction between ARF transcription factors and their repressors, the Aux/IAAs. ARFs bind to promoter elements and mediate transcription (Ulmasov et al., 1997a). Aux/IAAs bind to ARFs, negatively regulating transcription (Ulmasov et al., 1997b).

ARFs and Aux/IAAs are encoded by relatively large gene families comprising 23 and 29 members in Arabidopsis, respectively (Remington et al., 2004). Expression of functional proteins of both families throughout the plant is highly heterogeneous, and is heavily dependent on tissue type (Teale et al., 2006). It is this diversity of expression that is thought to play the crucial role in auxin's ability to control diverse cellular processes. Efforts to map the significance of individual ARFs and Aux/IAAs to specific auxin-dependent processes have revealed a high degree of functional specificity in both families, and led to the concept of an ‘auxin code’—a tissue-specific fingerprint of gene expression that initiates a defined developmental process (Weijers and Jürgens, 2004; Teale et al., 2006).

Though undoubtedly important, the relative significance of specific ARF–Aux/IAA interacting pairs (or indeed ARF and Aux/IAA homo- and heterodimers) to auxin signaling is not completely understood. Furthermore, it is widely believed that auxin is also able to have an effect through mechanisms distinct from ARF-mediated transcription, though none of these other pathways has been defined (Teale et al., 2006). Although much is known about auxin-mediated signal transduction, its complexity means that the molecular basis of how auxin can stimulate different processes in different organs and tissues remains ill-defined. Recently, many microarray experiments have analysed the response of Arabidopsis to auxin (Sawa et al., 2002; Pufky et al., 2003; Zhao et al., 2003; Armstrong et al., 2004; Himanen et al., 2004; Nemhauser et al., 2004; Redman et al., 2004; Nagpal et al., 2005; Okushima et al., 2005a, 2005b; Overvoorde et al., 2005; Vanneste et al., 2005; Wirta et al., 2005; Nemhauser et al., 2006). Although the main aim of these experiments was to find and classify auxin responsive genes, the fact that they varied significantly in their time of auxin exposure, auxin concentration, and tissue examined permits a more comprehensive analysis of gene regulation by auxin. We focus on auxin signaling and the regulation of cellular auxin concentration.

To investigate cross-talk with other hormonal signaling pathways, we analyzed the expression of genes associated with other hormones in response to auxin over a wide range of conditions. Hormone cross-talk after auxin application was related mainly with antagonism of auxin and cytokinin, synergism with ethylene, and a more intricate relationship with brassinosteroids. These data identify molecular targets for links between auxin and other hormones.

The concentration of bioactive auxin is routinely assessed with a synthetic promoter, DR5, containing multiple repeats of the AuxRE (Ulmasov et al., 1997b). Though this reporter has served the community very well, the recent observation of its activation by brassinosteroids raised questions regarding its specificity (Nemhauser et al., 2004). Therefore, a search for complementary auxin-sensitive genes was performed. This analysis revealed a small number of regulated genes, the transcription of which is induced specifically by auxin over a wide range of application conditions.


    RESULTS AND DISCUSSION
 TOP
 Abstract
 INTRODUCTION
 RESULTS AND DISCUSSION
 METHODS
 SUPPLEMENTARY DATA
 
The transcriptional response to the application of auxin has driven research into auxin signaling, with a specific and rapid induction of mRNA a key feature. Summarized in Figure 1 are the total numbers of genes found to be differentially expressed upon auxin application in Arabidopsis. These data represent seven independent transcript profiling experiments carried out under several auxin application conditions (Sawa et al., 2002; Pufky et al., 2003; Zhao et al., 2003; Armstrong et al., 2004; Himanen et al., 2004; Nemhauser et al., 2004; Redman et al., 2004; Nagpal et al., 2005; Okushima et al., 2005a, 2005b; Overvoorde et al., 2005; Vanneste et al., 2005; Wirta et al., 2005; Nemhauser et al., 2006). More genes were differentially expressed at high auxin concentrations (Figure 1A). As the length of time for which plants are exposed to auxin was increased, the number of regulated genes also increased. The primary response to auxin (as defined by those genes differentially expressed within 30 minutes) was almost entirely restricted to up-regulated genes. After longer exposures to auxin, a greater proportion of genes were down-regulated.


Figure 1
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Figure 1. Auxin-Related Microarray (Affymetrix ATH1) Experiments.

(A) Treatments covering different time exposures (short: 0.5 h, middle: 1–2 h and long: 3 h and longer) and IAA concentration (very low: 0.1 µM, low: 1 µM, middle: 5 µM, high: 10 µM) for whole seedlings.

(B) Additionally, we estimate tissue specificity of auxin response (roots, flowers and cell suspension culture) and the effect of auxin transport inhibitors on gene expression.

 
In order to understand better the auxin transcriptional response in Arabidopsis, we performed further similar experiments after the application of 1-NAA to cell suspension cultures. In this case, the number of differentially regulated genes was lower than that observed in roots. The overall trends in the numbers of differentially regulated genes remained similar to those observed in seedlings. Surprisingly, the earliest (15 minutes) auxin response was mostly down-regulation of gene expression.

Auxin-Related Transcriptomic Signature
Early Auxin-Responsive Genes
Three families of early auxin-responsive genes—auxin/indole acetic acid (Aux/IAA), GH3, and small auxin-up RNA (SAUR) (Guilfoyle, 1999)—are specifically induced by auxin within minutes. Here, we analyzed the expression of these genes together with three other gene families with products also known to play critical roles in auxin signaling and transport.

Aux/IAA
Of the 29 members of the Aux/IAA gene family in Arabidopsis, 28 were represented on the gene chips analyzed. Of these, 21 were differentially expressed in response to auxin under at least one condition. All but two of these genes (IAAs 27 and 28) were up-regulated. Eight genes (IAAs 1, 2, 3, 5, 11, 13, 19, and 29) form a cluster in which, except in the cases of IAA11 and IAA13, a short-term application of IAA was enough to alter their transcription (Figure 2).


Figure 2
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Figure 2. Meta-Signature of Auxin Response for ARF, Aux/IAA and LBD Families.

Gene expression up- or down-regulated (with at least a two-fold difference) by auxin or auxin transport inhibitors are presented in red and green, respectively. Only genes which are regulated under at least one set of conditions are presented.

 
A high heterogeneity was observed in the transcription of the Aux/IAA gene family in response to auxin. This depended both on tissue type (some were only regulated in the roots and others only in flowers), as well as duration and concentration of auxin exposure.

Aux/IAA proteins are also regulated, being specifically degraded in an auxin-dependent manner (Gray et al., 2001). The degron of domain II is an amino acid sequence necessary and sufficient for such rapid degradation (Ramos et al., 2001). This motif is wholly or partially missing from IAAs 20, 30, 31, 32, 33, and 34 (Dreher et al., 2006). Transcript of IAA33 was not detected (Remington et al., 2004). Transcripts encoding two of the five remaining stable Aux/IAA proteins were regulated by auxin, but only after either high auxin concentration or long exposure to auxin. Thus, up-regulation of Aux/IAA gene expression (especially at low and moderate auxin concentrations) applies mainly to the genes encoding the more unstable Aux/IAA proteins.

Comparing 1-NAA-treated with 1-NAA-starved suspension cultured cells showed that the expression of relatively few genes is differentially regulated. Of the most sensitive Aux/IAA mRNAs, IAAs 5, 1, 2, 11, and 13 are regulated quickly in cell suspension. These data were confirmed by real-time PCR (Supplemental Figure 4). In addition, the transcription of IAA20 and IAA30 was also induced after 1 h by 1-NAA (Supplemental Figures 4 and 5). All of these genes were expressed more strongly in seedlings at higher IAA concentrations.

ARF
ARFs form a family of 23 genes in Arabidopsis. In total, 20 ARF genes were represented on the gene chips analyzed, and the transcripts of three (ARF4, 16, and 19) were up-regulated in response to auxin under at least one condition (Figure 2). All three were up-regulated in the roots after both 2 and 6 h of exposure to 1-NAA, whereas ARF16 and ARF19 transcripts were also up-regulated in seedlings. ARF19 can be considered as the most sensitive gene, as increased transcription was also observed at 0.1 and 1 µM IAA. ARF16 mRNA was responsive only at 5 µM IAA, and at 1 µM after a long exposure time. ARF19 is most closely related to ARF7 and belongs to the ARF5–ARF8 clade (Remington et al., 2004). This group contains glutamine-rich middle regions that are thought to function as activators of auxin-responsive gene expression.

Regulation of Auxin Signaling
The response to auxin is defined not only by auxin concentration, but also by the specificity of the auxin-signaling network in different cells and tissues. The primary transcriptional response to auxin (as measured after short-time exposures to auxin) is relayed via Aux/IAA proteins. It is known that auxin signaling (including the transcription of certain Aux/IAAs) is quickly activated by the auxin-dependent degradation of proteins of this family (Gray et al., 2001). Not all Aux/IAAs respond to auxin, and those that do are regulated differentially in their sensitivity and responsiveness. For example, five Aux/IAAs (IAAs 9, 12, 18, 19, and 26) are induced by auxin in lateral roots, but not in cell suspension culture, under identical conditions. Of these, only IAA26 and IAA19 contain an AuxRE in their promoter, indicating that other tissue-specific factors direct auxin-induced gene expression. Some Aux/IAA genes are transcribed after a very short exposure to auxin. Despite the high variation in expression of Aux/IAA proteins throughout the plant (Teale et al., 2006), it is striking that at least one rapidly responding Aux/IAA is present in every tissue type. This provides a framework through which rapid responses to auxin can be managed in a tissue-specific manner. Such a regulatory mechanism involves increases in both Aux/IAA protein degradation and Aux/IAA mRNA expression. After a change in auxin concentration, a new equilibrium of cellular Aux/IAA protein concentration is found based on the difference between transcription of transcript and degradation of protein. Such equilibria enable the plant to respond very rapidly to changes in auxin concentration.

Aux/IAA proteins bind to ARFs (Tiwari et al., 2001). ARFs can be classified as either activators or repressors of the transcription of auxin-inducible genes (Ulmasov et al., 1999). In our analysis, three ARF genes were selectively regulated by auxin. Among these, ARF19 was the most sensitive to auxin. The fact that ARF19 is an activator of auxin-dependent transcription suggests that its role might be as a tissue-specific amplifier of the auxin signal. This mechanism can be considered as an example of a positive-feedback signaling loop, as previously suggested by Wilmoth et al. (2005). This might indicate that the function of ARF19 is especially important where there is a high demand for auxin signal transduction but also a limited capacity to maintain high auxin concentrations. The expression patterns for ARF16 and ARF19 in different organs and stages of development are similar (based on developmental Affymetrix Gene Expression Atlas) (Schmid et al., 2005; Teale et al., 2006). Similar patterns of expression of these genes are seen over different organs (high expression was found in senescent leaves, cauline leaves, carpels at later stages of flower development, roots and stems), suggesting that they work together. Although both respond to auxin, unlike ARF19, ARF16 is a repressor of auxin-dependent transcription. ARF19 is more sensitive to auxin than ARF16. ARF19-dependent auxin signal amplification could therefore be important at low auxin concentrations and at transient, short-term auxin exposures. At high auxin concentrations, a demand for the moderation of the auxin signal arises. Accordingly, ARF16 (and ARF4 in the roots) is transcribed. Competition among all three auxin-responsive ARF proteins for auxin-responsive cis-elements in the promoters of auxin inducible genes would then prevent further increases in the expression of auxin inducible genes.

SAUR
The SAUR genes encode highly unstable mRNAs (McClure and Guilfoyle, 1989; Franco et al., 1990) and form a large family in Arabidopsis comprising more than 70 members (Hagen and Guilfoyle, 2002). Within the SAUR gene family, two sub-clades can be identified (Figure 3). Clade I comprises six genes: SAURs 62, 64, 65, 66, 67, and 68, all of which were up-regulated by auxin under at least one condition (Figure 4). Clade I was strongly auxin-responsive. The second clade comprises 28 genes. Of this group, 10 were up-regulated by auxin in seedlings under at least one condition. Clade II can be considered as being moderately auxin-responsive.


Figure 3
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Figure 3. Neighbor-Joining Phylogenetic Tree Showing the Predicted Relationship between Members of the SAUR Family.

The alignment on which the tree is based was prepared using ClustalX 1.81. The phylograms were drawn using Tree-View 1.6.6 (http://darwin.zoology.gla.ac.uk/~rpage/treeviewx/). Auxin-up-regulated genes under one or more conditions are marked in yellow and red, respectively. Down-regulated genes are marked in blue. If an auxin response was observed only in the roots, the gene was marked with a capital ‘R’.

 


Figure 4
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Figure 4. Meta-Signature of Auxin Response for SAUR, GH3, PIN, LAX Gene Families, and Genes Participating in Auxin Biosynthesis.

 
Of the remaining 29 SAUR genes, eight were regulated by auxin under at least one set of conditions. In whole seedlings, two genes were regulated—SAUR 46 was up-regulated and SAUR 37 down-regulated. In the root, differential expression in response to auxin was predominantly down-regulation: four genes were down-regulated (SAURs 31, 36, 59, and 72) and two were up-regulated (SAURs 34 and 45). Auxin-up-regulated SAUR genes were co-expressed, with the highest expression observed in leaves and the lowest in roots and seeds (Supplemental Figure 1).

In contrast, the SAUR genes that cannot be grouped into clades I or II are relatively unresponsive to auxin and tend to have higher expression in the seeds and roots. Such distinct patterns of expression and auxin responsiveness suggest that clades I and II and the remaining SAUR genes have specific roles in leaves and roots, respectively. SAUR gene products could function as regulators of cell elongation (Knauss et al., 2003). Application of auxin in the range of concentrations studied usually acts to reduce root growth, whilst possibly stimulating growth of the upper-part of the plant (hypocotyls). High levels of expression of the SAURs of clades I and II in the shoot and their up-regulation by auxin also suggest that these genes could be important for the stimulation of shoot elongation. In contrast, high expression in the roots of those SAUR genes that do not belong to either clade, alongside their down-regulation by auxin, suggests their specific relevance to the auxin-dependent regulation of root growth.

Regulation of Auxin Concentration in Plants
GH3
IAA only affects plant growth in its unconjugated form. Thus, conjugation to a wide range of acceptor molecules is an important biological process in the regulation of active auxin. In Arabidopsis, GH3 genes encode a class of auxin-induced conjugating enzymes which has been divided into three groups, based on sequence similarity and substrate specificities (Staswick et al., 2005). In total, there are 19 GH3 genes in Arabidopsis. Of these, 16 were represented on the gene chips analyzed, with seven differentially expressed in response to auxin under at least one condition (Figure 4).

Group II enzymes catalyze reactions involving active IAA. Our analysis revealed that five GH3 genes are up-regulated in seedlings, with all five belonging to Group II. This suggests that Group II-mediated auxin conjugation is a specific response to auxin application, which also serves to decrease endogenous free-auxin in seedlings.

GH3.14 transcription was up-regulated only in the root. This gene belongs to Group III of the GH3 family, whose function has still not been identified. The response of auxin-sensitive GH3 genes to auxin is very rapid, with GH3.3 and GH3.4 also responding in suspension culture.

PIN
Of the eight PIN genes in Arabidopsis (Paponov et al., 2005) (all of which were represented on the gene chips analyzed), three were up-regulated by auxin at a transcriptional level—PIN1, PIN3, and PIN7 (Figure 4).

LAX
The auxin import transporter AUX1 is encoded by one of a family of four LAX genes, all of which were represented on the gene chips analyzed. Three members of this family were differentially expressed in response to auxin under at least one condition—AUX1, LAX2, and LAX3 (Figure 4). AUX1 is up-regulated in roots after 2 h of auxin application. Of the other family members, visible changes in transcription could be observed for LAX3 after a long exposure to auxin. Up-regulation of LAX2 could be observed after moderate auxin exposure times, but only at 5 µM IAA. All of the auxin-regulated LAX genes were up-regulated in the roots. The fact that not only auxin efflux, but also auxin influx carriers are up-regulated in response to applied auxin suggests that changes in auxin concentration are mediated not only on a cellular level, but also by increasing total auxin transport at a tissue level.

Auxin Transport Inhibitors
TIBA and NPA are both very well characterized inhibitors of auxin transport (Steeves and Sussex, 1989). However, the molecular targets of these compounds remain unknown. It is, however, clear that their modes of action are not identical. For example, at the same concentration, TIBA has a stronger effect than NPA. In accordance with this observation, TIBA regulated a far greater number of genes than NPA in the analyzed microarray data (Figure 1B). Further differences between the effects of TIBA and NPA have also been observed: at high concentrations, TIBA but not NPA was able to block 1-NAA-induced auxin-responsive BA::GUS expression (Oono et al., 2003), suggesting that TIBA may also have auxin antagonistic activity. ACL5 encodes a spermine synthase and represents the only gene both up-regulated by auxin and down-regulated by both TIBA and NPA—properties that would be expected of a protein involved close to, or at, the site of TIBA and NPA perception. Indeed, the increased thickness of veins and vascularization of leaves found in the acl5 mutant can be phenocopied in wild type by the chemical treatment of auxin transport inhibitors (Mattsson et al., 1999; Sieburth, 1999; Oono et al., 2003; Clay and Nelson, 2005).

IAA Biosynthesis
Of the 12 auxin biosynthetic genes represented on the gene chips analyzed, five are differentially expressed in response to auxin under at least one condition. Plants are able to synthesize IAA via a number of pathways (Woodward and Bartel, 2005). In the IAOx pathway, CYP79B2 and CYP79B3 were down-regulated after a long exposure to 1 µM IAA (Figure 4). It has been suggested that the enzymes encoded by these genes could be rate-limiting for auxin biosynthesis. Indeed, the cyp79B2, cyp79B3 double knock-out mutant has a phenotype suggestive of low cellular auxin concentrations, reduced IAA in certain growth conditions, a reduced amount of IAN, and no detectable indolic glucosinolates (Zhao et al., 2002).

In roots, SUR1, SUR2, and AMI1 transcripts were down-regulated by auxin (Figure 4). However, sur1 and sur2 show a high-auxin phenotype, suggesting that a decrease in the level of expression of these genes is not a regulatory response to high auxin concentrations (Delarue et al., 1998). AMI1 directly converts IAM to IAA in vitro (Pollmann et al., 2003), but the relative importance of this pathway to the total cellular auxin status is yet to be clearly established.

The Coordinated Control of Cellular Auxin Concentration
Dynamic auxin gradients underlie growth and development in plants (Teale et al., 2006). Such gradients are thought to be formed and maintained by the directional redistribution of auxin by highly specific auxin transporters, in response to both environmental stimuli and developmental cues. The series of events that follows the application of exogenous auxin gives an insight into the mechanisms that control the establishment and maintenance of such dynamic auxin gradients. After analyzing the temporal dynamics of the auxin response, it is possible to discern three phases of transcriptional control. After application of auxin, the quickest response is an induction of mRNA encoding auxin conjugation enzymes. The second response is an overall increase in the rate of auxin transport, as seen by the induction of transcripts encoding both auxin influx and efflux proteins. Thirdly, and only after a relatively long exposure to auxin, auxin biosynthetic gene transcription is down-regulated.

GH3 gene expression is induced in a quick and sensitive manner, giving tight control over free auxin concentration. That this is an important regulatory mechanism is borne out by the relatively high concentration of cellular conjugated IAA in comparison to free IAA (Woodward and Bartel, 2005). Such regulation of GH3 expression would therefore be predicted to temper the formation of auxin gradients. Auxin transporters can respond quickly to external stimuli and internal cues (Friml et al., 2002). If such responses are to form dynamic and tightly controlled auxin gradients, there also needs to exist a feedback mechanism for the rapid removal of auxin from cells after the establishment of an auxin gradient. As the first response to an elevated cellular auxin concentration, GH3-dependent auxin conjugation represents such a mechanism. In agreement with previously published data (Vieten et al., 2005), our analysis shows that auxin induces the expression of members of the PIN gene family. However, there is an increase in the transcription of not only efflux carriers, but also influx carriers. This implies that the effect of auxin is not limited to increasing its export from the cell, but rather serves to increase auxin flux through tissues. These data give additional support to the hypothesis that the auxin-responsive genes of the PIN and LAX families are particularly relevant to the control of auxin flux. These auxin-responsive auxin transporters might be particularly relevant to the control auxin gradients in those parts of the plant where auxin concentrations are relatively high, such as the root tip.

The inhibition of auxin biosynthesis can be considered as a secondary response to auxin, and therefore not immediately involved in the fine control of auxin concentrations. Rather, auxin biosynthesis could be involved in controling the overall amount of auxin present in the plant. To date, no enzymes with auxin deconjugation activity have been reported as being regulated by auxin. None of the ILR family of six IAA-amino acid hydrolase-encoding genes (five of which were represented on the chips analyzed) was responsive to auxin under any of the selected conditions. These data suggest that auxin deconjugation, although theoretically capable of significantly affecting cellular auxin concentration, does not have a significant impact on gradients of cellular auxin concentration. The factors that control auxin–conjugate hydrolysis are therefore not likely to include free auxin concentration, suggesting that auxin deconjugation is controlled indirectly.

The fact that the transcription of certain genes is triggered only at toxic auxin concentrations implies that there are some specific response mechanisms to very high auxin concentrations. Why plants need to respond to such a concentration is not clear; possibly, these responses are an adaptation to pathogen infection (Navarro et al., 2006). The high degree of variation in the auxin response and the tissue-specific responsiveness to auxin that plants display are based on a high degree of complexity within the auxin-signaling network. Identifying the crucial components of this network will form a framework in which we can better understand plant growth and development.

Identification of Additional Important Auxin Responsive Transcription Factors
Aux/IAAs form a family of genes well known to contain members that are up-regulated by auxin and whose products participate in transcriptional regulation. This group was strongly over-represented in all microarray experiments analyzed (Table 2). In Table 2, we also present other families of transcriptional regulators which are over-represented under at least two conditions of auxin treatment. This analysis revealed eight families. Among these, of special interest is the LOB domain (LBD) family. This family was frequently over-represented under different auxin conditions. The most sensitive and quickest responding genes in the LBD family are LBD29 and LBD16 (Figure 2). Both genes were up-regulated by auxin after 30 minutes.


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Table 1. Overview of Auxin-Related Experiments Included in the Analysis.

 


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Table 2. The Families of Transcription Factors, Differentially Expressed Members of which Are Over-Represented under at Least Two Auxin Inducible Conditions.

 
The LBD family comprises 42 genes in Arabidopsis. In total, 26 were represented on the gene chips analyzed. Of these, 11 were differentially expressed in response to auxin under at least one condition, indicating that the LBD gene family is relevant to auxin signaling. These auxin-responsive LBD genes cluster into class Ia (Iwakawa et al., 2002); it contains 29 members, of which 18 are represented on the chips analyzed, with eight differentially regulated by auxin under at least one condition. Three members of class II (LBD37, LBD40 and LBD41) were also differentially regulated by auxin (Figure 2).

ASYMMETRIC LEAVES2 (AS2/LBD6) (the first member of the LBD family to be characterized) also belongs to class Ia (Iwakawa et al., 2002). However, it is not auxin-responsive in the experiments analyzed and does not cluster with the other auxin responsive genes (Supplemental Figure 2). AS2 showed low expression in the root and high expression in photosynthetic tissue. Supporting these expression data, the mutant phenotype was observed only in leaf-like organs, and not in the root (Iwakawa et al., 2002). In contrast, the most auxin-responsive genes of the LBD family were co-expressed in the roots (Supplemental Figure 3).

A recent study has identified members of this family as part of the auxin response in lateral root formation, confirming their auxin-responsiveness (Okushima et al., 2007). Together with our analysis, these data suggest a strong connection between auxin and the LBD family.

Hormone Cross-Talk
As expected, the strongest effect of IAA was on genes annotated as participating in hormone-dependent signaling pathways. Genes belonging to auxin-dependent pathways was the most over-represented group (Table 3). Here, we present results concerning the interaction between auxin and other plant hormones. Below, auxin-responsive genes are identified by either their responsiveness to another specific hormone, involvement in that hormone's synthesis or degradation, or by their association with its signal transduction pathway (Thimm et al., 2004).


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Table 3. Main Gene Ontology Categories Extracted from MapMan Annotation, which Are Significantly Over-Represented under at Least Two Conditions.

 
In many cases, different plant hormones affect the same cellular processes. Determining to what extent the signaling pathways of different hormones overlap is crucial if we are to understand the regulation of plant development (Nemhauser et al., 2006). An analysis of the regulation by auxin of genes that are associated with other plant hormones suggests how hormone signaling pathways interact.

Cytokinin
The interaction of auxin and cytokinin controls many aspects of plant growth and development, including shoot and root development. Of a total of 49 selected cytokinin-related genes, seven were differentially expressed in response to auxin under at least one condition. The expression of CXK6 (Figure 5), encoding a cytokinin oxidase, was exclusively induced by auxin. Notably, this induction occurs rapidly and at the lowest auxin concentration tested. Auxin could decrease the concentration of cytokinin in the plant, by either decreasing biosynthesis (Nordström et al., 2004) or increasing catabolism. CKX6 mRNA is up-regulated by auxin in all conditions tested in both seedlings and roots, except after a long exposure to a low IAA concentration. Over-expression of CKX6 leads to a reduced cytokinin concentration and its associated phenotypic changes (Werner et al., 2003). These data support CKX6 as a candidate for the central regulator of the interaction between auxin and cytokinin. Cytokinin signaling is modulated by the ARR family of transcription factors. One gene (ARR7) had a varied response to auxin, being down-regulated in the roots and up-regulated in flowers. Four ARR genes were down-regulated in the roots by auxin—ARRs 5, 6, 7, and 11. Three of these four genes (ARRs 5, 6, and 7) belong to the type A ARR family, which is also rapidly regulated by cytokinin. Down-regulation of type A ARR genes has been observed in the cytokinin-deficient 35S:AtCKX1 line (Brenner et al., 2005). Such regulation of ARRs 5, 6, and 7 provides a link between auxin signaling, cytokinin signaling and meristem identity (Leibfried et al., 2005). Together, these results suggest that auxin signaling influences cytokinin concentration via CKX6, and consequently ARR activity.

Ethylene
Of the 107 selected ethylene-related genes, 13 were differentially expressed in response to auxin under at least one condition (Figure 5). Transcripts of a large majority of these genes were up-regulated, with the genes most sensitive to auxin encoding ethylene biosynthetic enzymes. Application of auxin induced the expression of three ACS genes (1-Aminocyclopropane-1-carboxylate synthase), ACSs 6, 8, and 11, the products of which catalyze the rate-limiting step of the ethylene biosynthetic pathway (Yamagami et al., 2003). Real-time PCR confirmed a transient increase in the amount of ACS6 transcript in suspension cell culture after treatment with 1-NAA (Supplemental Figure 5). Another potential auxin-responsive ethylene biosynthesic enzyme—the ACC oxidase-like At5g43450—catalyses the last step in ethylene biosynthesis, and was up-regulated only in the roots.


Figure 5
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Figure 5. Meta-Signature of Auxin Response for Cytokinin, Brassinosteroid, Gibberellin, Ethylene, ABA, Salicylic Acid, and Jasmonate-Related Genes. Genes were classified according to the MapMan ontology and marked respectively: blue-synthesis, degradation; black-signal transduction; red-induced.

 
One of the ethylene genes most sensitive to auxin was AT5G67430 (GNAT), encoding an N-acetyltransferase (Figure 5). One member of this family (HOOKLESS1) has been shown to be a key integrator of the auxin- and ethylene-signaling pathways (Lehman et al., 1996). hookless1 (hls1) is deficient in an N-acetyltransferase that is ethylene-inducible and has a GCC-box in its promoter (Stepanova and Ecker, 2000). Auxin has been shown to affect ethylene synthesis through an activation of ACS (Tsuchisaka and Theologis, 2004), with gene-specific and cell-type-dependent IAA-induced ACS expression across the root tip zone. Our analysis revealed three auxin inducible ACS genes, indicating a synergism between auxin and ethylene action. The fact that the transcription of two of these (ACS6 and ACS8) (in addition to that of ACS2) is impaired in the developing siliques of arf2-6 (Okushima et al., 2005a) supports the importance of tissue-specific auxin signaling for ethylene biosynthesis.

The second group of auxin-responsive ethylene genes is involved in signaling. These genes responded more slowly and typically needed higher auxin concentrations for their transcription. Four ethylene response factors (ERFs) were auxin-responsive—AT5G25190 (ERF), AT5G18560 (ERF), ERF6, and ERF11. The auxin-responsive ERS2 encodes an auxin-responsive ethylene receptor related to bacterial two-component histidine kinases (Hua et al., 1998). One ERF gene product (AT5G51190 (ERF)) showed a variable response to auxin and one (AT5G07580 (ERF)) was down-regulated after auxin application. In general, an up-regulation of ERF transcription factors and an up-regulation of the type-II ethylene receptor ERS2 indicate that auxin treatment renders plants more sensitive to ethylene. That only a small subset of ERF genes is induced by auxin facilitates further investigation into processes under joint control of both hormones.

Brassinosteroids
Of the 46 selected brassinosteroid-related genes, eight were differentially expressed in response to auxin under at least one condition. BAS1 and SOB7 (encoding enzymes that inactivate brassinosteroids) transcription was up-regulated at short (BAS1) or moderate to long (SOB7) IAA exposures (Figure 5). Thus, the most rapid response of brassinosteroid-related genes to auxin leads to a decrease in brassinosteroid concentration. Both genes modulate photomorphogenesis (Turk et al., 2005), and act redundantly in three light-induced processes—the induction of cotyledon expansion, the repression of hypocotyl elongation, and control of flowering time. After a longer IAA treatment (and after the incubation of roots with 1-NAA), DWF4 transcription was up-regulated. The encoded enzyme catalyzes a flux-determining step in the brassinosteroid biosynthetic pathway (Choe et al., 1998), indicating that the relationship between auxin and brassinosteroid biosynthesis is more complicated than simply synergism or antogonism.

Auxin not only increases transcription of brassinosteroid biosynthetic genes, but potentially also increases the plant's sensitivity to brassinosteroids. Both after long-term auxin exposure and at high auxin concentrations (5 µM), the transcription of BRL3, which encodes a functional receptor for brassinosteroids (Cano-Delgado et al., 2004), was up-regulated.

Transcriptional responses to auxin and brassinosteroid application are intertwined, with many examples of synergism between the respective signaling pathways (Nemhauser et al., 2004). Our analysis revealed a complex relationship between auxin application and brassinosteroid-related gene expression, implying an influence of auxin both over brassinosteroid cellular concentration and sensitivity. This relationship is quite complicated (at different concentrations, auxin induces the transcription of genes encoding enzymes involved in both brassinosteroid biosynthesis and breakdown) and it could reflect a high degree of tissue specificity. Indeed, it has been demonstrated that DWF4—an auxin-induced brassinosteroid biosynthetic enzyme—has a specific effect on tropism in the hypocotyls via ARF7 and IAA19 (Nakamoto et al., 2006).

Gibberellin
Of the 49 gibberellin (GA)-related genes, five were differentially expressed in response to auxin under at least one condition (Figure 5). DTA1 encodes an enzyme with GA 2-oxidase activity. Over-expression of this gene in Arabidopsis reduces endogenous GA levels, causing a GA-deficient phenotype (Wang et al., 2004). The transcription of two GA biosynthetic genes is regulated by auxin in ArabidopsisGA20ox2 (a 20-oxidase) and GA4 (a 3β-hydroxylase). That GA20ox2 was up-regulated by auxin has been recently confirmed elsewhere (Frigerio et al., 2006). These data suggest that the GA response upon auxin application could also be tissue-specific. In support of this hypothesis are the observations that in roots, only DTA1 (and not GA20ox2) was up-regulated, and GA4 (Chiang et al., 1995) was down-regulated specifically. Two GA-regulated genes (GASA5 and GASA1) were also regulated by auxin. They encode small proteins of unknown function.

Decapitation experiments have shown that in pea, GA1 biosynthesis requires auxin (Ross et al., 2000). Our analysis reveals no clear relationship between auxin application and gibberellin biosynthesis in Arabidopsis. However, auxin application does differentially regulate the transcription of GA biosynthetic genes, including the inactivating GA 2-oxidase. The effect of auxin on cellular GA concentration is therefore specific, depending on auxin concentration, time of auxin exposure, and tissue type.

ABA, Salicylic Acid and Jasmonate
Of the 45 abscisic acid-related genes, two were differentially expressed in response to auxin under at least one condition (Figure 5). Both of these belong to the group of ABA-responsive genes. AT5G08350 was up-regulated in roots and flowers, and AT3G02480 was down-regulated after a long exposure to IAA in seedlings 0.1 µM and in roots.

Of the 19 salicylic acid-related genes, two were differentially expressed in response to auxin under at least one condition (Figure 5). Both are involved in salicylic acid metabolism.

AT5G08350 has very high homology to AtSGT1, which participated in the glucosylation of salicylic acid (Song et al., 2006).

Of the 32 jasmonate-related genes, one was differentially expressed in response to auxin (Figure 5). Encoding an allene oxide cyclase, AOC4 was up-regulated by auxin in the root. The Arabidopsis genome contains four genes that encode this enzyme, which catalyzes an essential step in jasmonic acid biosynthesis.

Auxin-Sensitive Marker Genes
Our understanding of auxin signaling has been increased significantly by the availability of the DR5 marker—a synthetic promoter containing repeats of the AuxRE, to which the ARF proteins bind (Ulmasov et al., 1997b). However, several investigations have demonstrated that DR5 is also under the control of brassinolide (Nakamura et al., 2003; Bao et al., 2004; Nemhauser et al., 2004), leaving the search for more specific and more sensitive auxin markers ongoing. Significant progress in this direction was made by Nemhauser et al. (2006), who, on the basis of one experiment and using strict criteria for differential expression, selected ‘robust hormone-responsive’ genes. There, genes found to be regulated by a single hormone were labeled as marker genes. Nemhauser et al. (2006) found 54 up- and three down-regulated marker genes for auxin. As these data identify a fairly high number of genes, we decided to make an even more robust selection of genes based on seven experiments. We selected candidates on the basis of their differential expression over all seven data sets available for whole seedlings. Here, we assume that transcription of the most specific and sensitive auxin-responsive genes is up-regulated by auxin. This assumption is justified by the observation that the first response to auxin is almost exclusively an up-regulation of gene expression (Figure 1A). We found three genes that belonged to both a previously published list of auxin marker genes (Nemhauser et al., 2006) and to the lists of genes regulated in the six other conditions for which data are available. The list of proposed auxin-sensitive marker genes is given in Figure 6. When fewer conditions were grouped, more auxin-responsive genes were found. The numbers of auxin-regulated genes under six, five, four, and three conditions were three, seven, nine, and 17, respectively. These genes can be considered to be secure auxin markers, as they are specifically up-regulated under a wide range of conditions. For cell suspension culture, we could select three genes which we could consider as auxin markers for the MMd2 cell line (Menges and Murray, 2002).


Figure 6
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Figure 6. Auxin-Specific Markers in Whole Seedlings that Are Up-Regulated in at Least Four Selected Auxin Treatments.

 
Low tissue specificity is also a requirement for a reliable auxin marker; that is, it must be induced by auxin in all parts of the plant. An analysis of the expression of these genes in different tissues (roots, flowers, and cell suspension culture) showed that none of the identified auxin-responsive genes is expressed throughout the plant. All genes selected are up-regulated in the roots and none is auxin-responsive in flowers. This means that selection of the auxin marker is inevitably influenced by the initial experimental conditions.


    METHODS
 TOP
 Abstract
 INTRODUCTION
 RESULTS AND DISCUSSION
 METHODS
 SUPPLEMENTARY DATA
 
Suspension Culture Experiment
For the auxin starvation and re-supply experiment using Arabidopsis cell culture, fast-growing cell line MM2d was used (Menges and Murray, 2002), which was selected from a cell suspension originally produced from Landsberg erecta stem explants by May and Leaver (1993). MM2d was maintained as previously described by diluting weekly 3.5 ml culture into 100 ml of fresh MSS medium (1 MS-salt, supplemented with 3% (w/v) sucrose, 0.5 mg l–1 napthalene acetic acids (NAA) and 0.05 mg l–1 kinetin (Menges and Murray, 2002). MM2d cells are grown in a darkened New Brunswick Innova Model 4230 incubator shaker with 19 mm orbit at 130 rpm at a temperature of 27°C. To remove remaining NAA from the medium prior auxin starvation, 40 ml of an early stationary phase culture (7 d after previous subculture) were gently washed through a nylon net in a home-made filtration unit (mesh size 47 µM) (Menges et al., 2006) with a total of 1 l of MSS-medium (lacking NAA) by changing the medium several times. After approximately 15 min, the cell suspension was transferred to Falcon tubes and finally washed by centrifugation for 1 min at 1500 rpm (387 g), with no brake force applied. The cell pellet was re-suspended in 40 ml MSS-medium (supplemented with 0.05 mg l–1 kinetin but lacking NAA); 20 ml each of the washed and pooled cell suspension was transferred into 100 ml of fresh MSS-medium (lacking NAA) to achieve a dilution factor of approximately 1:5, and incubated further at 27°C, 130 rpm in the dark for 4 h. After 4 h of auxin starvation, NAA was added to one batch to achieve a final concentration of 0.5 mg l–1, whereas the second batch remained untreated (no NAA control). For transcript profiling analysis using Affymetrix full genome ATH1 arrays, samples were taken at 15 min, 30 min, 1 h and 2 h after NAA addition. RNA was extracted as previously described (Menges and Murray, 2002).

Microarray Data
Microarray data of published experiments (1–4, 6, 7) were downloaded from www.ncbi.nlm.nih.gov/geo/. The data of experiments 5 and 8 were downloaded from http://www.Arabidopsis.org/. For details of these experiments, we refer to the original publications (Table 1).

We performed a comparative analysis on various auxin-related data sets to obtain a global insight into the complexity of the transcriptomic responses of plants to auxin (Figure 1). Because most auxin experiments were done with Affymetrix full genome ATH1 arrays, and to exclude questions about cross-platform comparability of microarray technology, we exclusively used Affymetrix chips for our analysis. Table 1 summarizes the nine selected experiments. Five data sets were obtained by application of IAA to seedlings, one to flowers, one by application NAA to root segments, one by application NAA to suspension culture, and one by application auxin transport inhibitors to seedlings (Table 1).

TaqMan Real-Time PCR Assay
Total RNA was isolated from cell suspension culture MM2d grown as described above. Samples were taken after 1 and 2 h incubation with or without NAA. Total RNA was isolated using Trizol (Invitrogen) according to the manufacturer's protocol. The isolated RNA was digested with DNAse I and purified with the Qiagen RNeasy mini kit (Qiagen, Hilden, Germany). First-strand cDNA synthesis was performed using the TaqMan reverse transcription reagents (Applied Biosystems, Darmstadt, Germany) using hexamers for transcription. The cDNA synthesis was done for all genes together in order to avoid variation caused by several reverse transcriptions. MGB-TaqMan probes and primers (Table 4) were designed based on the software Primer Express 2.0 (Applied Biosystems) having 6 FAM and VIC reporter (5'end) dyes; 50 ng cDNA was used for TaqMan real-time PCR (ABIPrism 7000) using a triplet reaction for every treatment. In order to normalize the variation between cDNA, the expression level of 18S rRNA was used as housekeeping control. The relative quantities of the transcripts were calculated by using the standard curve method (Livak, 1997) relative to the untreated sample respectively at 1 and 2 h. Means and SDs (n = 3) are present on the figures.


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Table 4. Primers and Probes for TaqMan Real-Time PCR.

 
Short Explanation of Analysis
We used the log2 scale RMA procedure for background correction and normalization for all experiment (Irizarry et al., 2003). Data for experiment 4 were only available in RMA normalized form. The R environment (Ihaka and Gentleman, 1996) was used for running the RMA program. Expression values were re-scaled so that the fold change between treatment and control was not changed, but the average level of intensity of all genes for all experiments was corrected at the level of experiment 1 (Okushima et al., 2005b). Then we followed the analysis suggested by Okushima et al. (2005b). A hybridization signal <5.64 (= log250) was considered as background; all signals <5.64 were converted to 5.64 before further analysis. Following data processing, fold-change values were used as a selection criterion for differential transcripts. Due to the heterogeneity of the experimental design, no robust statistical analysis could be performed. Therefore, only the use of relative expression data was appropriate, although the possibility of false positives and negatives associated with this approach remains (Gadjev et al., 2006). Although fold-changes do not control the variance, and so are susceptible to outliers, this method selects gene lists in a similar manner to the rank product method. Rank product is considered to be the best method by which to compare experiments with limited numbers of samples and/or noisy data sets (Jeffery et al., 2006). Fold-changes were calculated for all time points in all nine individual experiments, using the expression value of the treated samples relative to the control (mock-treated) samples. For experiment 2, the control was time zero. The threshold for up-regulated or down-regulated responses was set at a two-fold change in expression. The genes represented on the Affymetrix full genome ATH1 arrays were assigned to functional categories using the MapMan hierarchical ontology (http://gabi.rzpd.de/projects/MapMan). Over-representation of the genes assigned to a functional category (BIN or sub-BIN) was assigned at P < 0.05 after Benjamini Hochberg correction.

Data of log2(intensity) after normalization and scaling and log2(fold change) of gene expression with and without auxin (e.g. auxin inhibitors) are present in Sheet1.xls. AGI numbers for each of the genes mentioned in the manuscript are present in Sheet2.xls.


    SUPPLEMENTARY DATA
 TOP
 Abstract
 INTRODUCTION
 RESULTS AND DISCUSSION
 METHODS
 SUPPLEMENTARY DATA
 
Supplementary Data are available at www.mplant.oxfordjournals.org


    Acknowledgements
 
We thank R. Hertel and members of our laboratory, particularly Arthur Molendijk for critical reading of the manuscript. IP thanks the Microarray Data Analysis Resource (NGFN II, SMP Bioinformatics, Subproject 3.2) for its help in the statistical microarray analysis. The authors thank the cell biology department of Peter Beyer for providing the Real-Time PCR facilities and in their introduction by Dr Ralf Welsch. We are grateful for the invaluable resources available on the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov) and TAIR (http://www.Arabidopsis.org) websites. Our work was supported by the Deutsche Forschungsgemeinschaft (SFB 592), ESA, EU, FCI, and the Landesstiftung Baden-Württemberg GmbH. KP is particularly grateful for having had the opportunity to contribute to the DFG RTD network ‘Molecular Mechanisms of Phytohormone Action’. No conflict of interest declared.


    Notes
 
2 These authors made equal contributions to this work. Back

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