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      Auxin: small molecule, big impact

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          Abstract

          Auxin research touches on a very wide variety of processes in plant development, and correspondingly a range of systems and approaches is revealing new understanding. This special issue spans this range, from research on mosses and liverworts which is revealing evolutionary aspects to the exquisite detail of signalling processes shown in Arabidopsis and agronomic potential in crops. As well as compiling and analyzing our current knowledge on auxin action, the reviews also provide a roadmap for future research. Since its discovery nearly a century ago (Thimann and Koepfli, 1935), auxin has risen to prominence as a plant signalling molecule, inspiring many to study its secrets. Past decades have seen a number of breakthroughs in the identification of a deceptively simple transcriptional response pathway (Weijers and Wagner, 2016), as well as cellular and molecular mechanisms of directional auxin transport (Adamowski and Friml, 2015), synthesis and inactivation (Korasick et al., 2013). At the same time, auxin action has been reported in most, if not all, growth and developmental processes (Weijers and Wagner, 2016), in interactions with other hormonal signalling pathways (Vert and Chory, 2011), and even in the interaction with beneficial or pathogenic microorganisms and viruses (Boivin et al., 2016). In fact, it is difficult to describe any plant process without some direct or indirect reference to auxin. The set of papers in this issue reflects this breadth of auxin research, and provides in-depth reviews in a wide range of aspects of auxin biology. While some of these represent ‘classical’ aspects of auxin action, others discuss recent progress in areas where the involvement of auxin has not yet been characterized in detail. Auxin maxima and cell growth Arsuffi and Braybrook (2018) review research on one of the earliest, classical physiological responses to auxin: cell wall acidification leads to altered growth. This response has been studied for decades, initially using various physiological assays, which led to the formulation of a simple model. This model has seen many changes over the decades, mostly through genetic analysis of the auxin response. The authors bring together original ideas with recent exciting findings to propose a more complex scheme of cell wall acidification, and also highlight a number of outstanding questions. Wang and Jiao (2018) discuss the role of auxin transport in shoot meristem development. One of the first mutants identified in the auxin field was pin-formed1, which produces naked, pin-like stems and no flowers. PIN1 was later shown to encode an auxin transport protein, and mutations that reduced the biosynthesis of, or response to, auxin were found to cause similar defects. Thus, auxin is a potent regulator of flower formation at the shoot meristem. In recent years, genetic approaches, gene expression analysis and live imaging have led to new models as to how the local accumulation of auxin at the shoot meristem is controlled, and how these maxima trigger organ formation. Wang and Jiao provide an overview of this aspect of auxin action. Similar to the shoot, local auxin accumulation in the root also has strong morphogenetic potential. Auxin maxima trigger several successive steps in the formation of lateral roots along the primary root. Separate responses provide context to the priming, initiation and emergence of lateral roots, and both the auxin response components and the downstream genes of these different steps have been characterized in recent years. Du and Scheres (2018) describe these latest findings and provide an integrated view of auxin-dependent lateral root formation. Much auxin-related research has focused on the activity of the dominant naturally occurring auxin: Indole-3-Acetic Acid (IAA). Several synthetic analogues [including 2,4-dichlorophenoxyacetic acid (2,4-D) and 1-naphthaleneacetic acid (NAA)] have also been widely used. However, there are other naturally occurring molecules with auxin activity, and indole-3-butyric acid (IBA) has been the subject of active investigation for many years. IBA is nearly identical to IAA with the exception of an added CH2 group, yet the activity of IBA is rather different than IAA. Frick and Strader (2018) discuss the roles of IBA as a tightly regulated auxin storage form that allows spatio-temporal control of auxin levels during plant development, particularly in the elaboration of the root system. A key question they discuss is whether IBA action fully depends on enzymatic conversion to IAA. In addition, the authors suggest that the liberation of active auxin from IBA can be strongly modulated by environmental stresses. The nuclear auxin response Auxin is well known for its ability to regulate numerous growth and developmental processes. Many such outputs depend on the modification of gene expression programs. Auxin-dependent AUXIN RESPONSE FACTOR (ARF) transcription factors are the final step that selects which genes are auxin-regulated and how. Roosjen et al. (2018) provide an extensive overview of the ARF transcription factor family, their specificity of DNA binding and modes of action. The authors propose that ARFs possess an intrinsically disordered domain and speculate on how this might mediate gene regulation. The ARFs have surfaced as the key auxin-dependent transcription factors, and a binding site for these proteins has been defined. However, many auxin-regulated genes do not display clear ARF target sites. Cherenkov et al. (2018) describe a bioinformatic meta-analysis of a large number of auxin-related transcriptomics datasets to identify hexamer sequences that are enriched in auxin-dependent genes. In addition to the well-known ARF binding site, the authors have found several other motifs that are associated with auxin responses. These motifs can be correlated to chromatin properties, as well as to potential binding of other transcription factors. This offers a framework to consider new regulators of auxin-dependent genes. Interactions with other hormones, other organisms and the environment Through its central position in the regulation of growth and development, the auxin response is modulated by many other signalling pathways. Han and Hwang (2018) provide an overview of the intersections and interactions of the auxin response pathway with other hormonal signalling components. Mroue et al. (2018) review the way in which environmental triggers modulate auxin homeostasis, and focus on the modulation of auxin biosynthesis. Clearly, there is widespread regulation of auxin homeostasis by a variety of environmental stimuli, thus translating external conditions to coordinated changes in growth and development. One such environmental condition is light quality. The ratio of red to far-red light is sharply decreased when plants are shaded by neighbours. Plants detect these differences in light quality and use this as a signal to enhance stem growth. Iglesias et al. (2018) describe how light quality directs altered growth through changing auxin biosynthesis and transport. A central module that connects light receptors to a light-regulated transcription factor and to auxin biosynthesis genes plays a central role in this response and, at the same time, light-regulated auxin transport changes help create local auxin maxima for directional growth. Biotic environmental factors also modulate plant growth and development through auxin activity. A good example is the formation of root nodules by legumes in symbiosis with Rhizobium bacteria. Kohlen et al. (2018) describe how the interaction between root cells and bacterium-derived and bacterium-induced signals involves changes in auxin transport and response to locally activate cell divisions and generate a nodule. Finally, the interaction with bacterial plant pathogens also involves auxin activity. A famous example is the crown gall-inducing Agrobacterium tumefaciens, which transfers hormone biosynthesis genes, including auxin biosynthesis genes, to the plant genome and through this triggers cell division. However, there are several other cases of bacteria manipulating auxin action, for example by modulating the auxin response to alter growth and development or to subvert defence responses. Kunkel and Harper (2018) discuss the ways in which bacterial pathogens manipulate auxin biology to facilitate their survival and viability in plants. Evolution and divergence of auxin biology Most auxin research has been performed in the dicot model species Arabidopsis thaliana, although earlier, physiological research was done in a range of species. Arabidopsis is not of agronomic importance, but clearly the significant impact of auxin action throughout plant life means that agronomically relevant traits in crops are also influenced by auxin. Wang et al. (2018) review what rice research has contributed to our understanding of auxin biology and, more importantly, discuss which quality and yield traits in rice are controlled by auxin. This paves the way for targeted crop modification based on changing auxin activity. Auxins have been used in agriculture and horticulture for decades, both to control plant growth and notably also to kill weeds. Auxin-based herbicides are plentiful, but the chemical basis for herbicide action is not always obvious. Quareshy et al. (2018) have compiled chemical and physical information on all major auxinic herbicides and describe a chemi-informatic analysis of these properties in relation to the herbicidal activity of the compounds. This rich source of information will help further develop agrochemistry based on auxin action. Given the broad range of activities in flowering plants, a central question in auxin biology is how this system emerged and evolved complexity. Two reviews discuss auxin activity and response in basal land plants. Thelander et al. (2018) review how auxin controls development in the moss Physcomitrella patens. Essentially all growth and developmental programs depend in one way or another on auxin biosynthesis, transport and/or responses. Interestingly, the auxin response system in this moss is considerably simpler than those in flowering plants, and hence this model system should facilitate understanding of how diversity in auxin responses is generated. Kato et al. (2018) mostly focus on the liverwort Marchantia polymorpha, which probably diverged before the mosses and has an even simpler auxin response system, and discuss the conservation of mechanisms in auxin responses. New tools Drugs have been instrumental in dissecting mechanisms of auxin action. Compounds that inhibit auxin transport, for example, have helped explain how it is transported and how this controls growth and development. Curiously though, the molecular mechanism through which such compounds act is not always clear, even if they are widely used. Teale and Palme (2018) review the current literature on the working mechanisms of 1-N-naphthylphthalamic acid (NPA), a widely used auxin transport inhibitor. In addition to the ‘classical’ compounds used in auxin biology, there have been several endeavours to screen for novel small molecules that modify auxin transport, biosynthesis or responses. Clearly, well-characterized compounds will be invaluable tools in generating an even deeper understanding of auxin action, much as auxin transport inhibitors have done in the past. Ma et al. (2018) discuss the chemical biology and chemical genetics approaches that have been taken to dissect auxin action. Outlook The papers in this special issue compile and analyze our current knowledge of auxin action. They also provide a roadmap for future research. Clearly, the mechanistic understanding of auxin biosynthesis, breakdown and response has been developed to nearly atomic resolution through the availability of crystal structures of the main proteins involved (Parcy et al., 2016). Similar molecular – and thus mechanistic – detail is lacking for auxin transport, and it is evident that such information would help us understand not only the mechanisms of auxin transport, but also its regulation by various endogenous and exogenous signals. Perhaps such structural information would also help rationalize the effects of well-established drugs and small chemical compounds on auxin transport. After a strong focus on generic principles in auxin biology, recent years have brought an appreciation of the diversity of hormone action, in terms of both the multiple growth and developmental responses in model plants and the evolutionary context of auxin action. Now that genomic technologies allow the analysis of the local auxin response (Bargmann et al., 2013; Möller et al., 2017), it is likely that the molecular basis for the diversity of auxin-triggered events during development will become clearer. At the same time, genomic technologies are allowing the extraction of detailed information from a much wider range of species than just the genetically tractable models. This allows the first glimpses into cross-species diversity and evolution of auxin action, but it is expected that coming years will bring deep insight into the origin and evolutionary history of auxin action as well as helping us to understand species-specific aspects of auxin biology. These, in turn, may help this research field to turn a rich history of discovery into approaches to improve crops for the future.

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          Auxin biosynthesis and storage forms.

          The plant hormone auxin drives plant growth and morphogenesis. The levels and distribution of the active auxin indole-3-acetic acid (IAA) are tightly controlled through synthesis, inactivation, and transport. Many auxin precursors and modified auxin forms, used to regulate auxin homeostasis, have been identified; however, very little is known about the integration of multiple auxin biosynthesis and inactivation pathways. This review discusses the many ways auxin levels are regulated through biosynthesis, storage forms, and inactivation, and the potential roles modified auxins play in regulating the bioactive pool of auxin to affect plant growth and development.
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            A map of cell type-specific auxin responses

            Introduction One of the main organizational cues in plant development is the signaling molecule auxin. A remarkable facet of auxin's effect on plant development is the broad range of processes regulated by this simple compound (Vanneste and Friml, 2009). In meristems, auxin is a central modulator of growth and cellular differentiation (Bennett and Scheres, 2010). Auxin concentration gradients are maintained by active polar transport and have been proposed to give positional information that stages development and maturation in these growth centers (Friml et al, 2002; Benkova et al, 2003; Bhalerao and Bennett, 2003; Galinha et al, 2007; Ding and Friml, 2010; Dubrovsky et al, 2011). Although auxin itself cannot be directly visualized, meristematic auxin gradients have been inferred from mass spectrometric measurement of tissue sections (in the Pinus sylvestris cambial meristem) and isolated cell types (of the Arabidopsis thaliana root apical meristem (RAM)) (Uggla et al, 1996; Petersson et al, 2009). A recently developed biosensor, DII-Venus (consisting of a fluorescent protein fusion of a labile component of the auxin perception and signaling machinery), has provided a new level of sensitivity in determining the distribution of auxin signaling activity in meristems (Vernoux et al, 2011). Readout of this sensor in the RAM suggests that there are cell type-specific aspects to auxin perception. In addition, it shows graded levels of auxin signaling intensity in the meristematic stele that are in line with a proximo-distal gradient of auxin itself (Supplementary Figure S1A; Brunoud et al, 2012). However, we lack an understanding of how cells interpret an auxin gradient in their broad transcriptional output (Overvoorde et al, 2010). Localized auxin signaling output can be observed by visualizing the transcriptional response to auxin. DR5, a synthetic auxin-responsive promoter, driving a reporter gene (e.g., green fluorescent protein (GFP)) is often used as a proxy for the transcriptional auxin response (Supplementary Figure S1B; Ulmasov et al, 1997; Heisler et al, 2005). DR5 displays high expression in the tip of the RAM (specifically in the columella, QC and developing xylem), but its expression does not effectively match cell type-specific auxin measurements (Petersson et al, 2009) or fully complement DII-Venus levels in the RAM (Brunoud et al, 2012). Furthermore, the promoters of endogenous auxin-responsive genes, for example, SMALL AUXIN UP RNA (SAUR), AUXIN/INDOLE-3-ACETIC ACID INDUCED (Aux/IAA), BREVIS RADIX (BRX) or PLETHORA (PLT) genes, have been used to report the spatial influence of an auxin gradient on gene expression (Li et al, 1991; Galinha et al, 2007; Grieneisen et al, 2007; Santuari et al, 2011). However, these constructs give differing views of auxin-response distribution, with some showing an archetypal expression pattern similar to DR5 and others with a more graded expression in the proximal meristem. Hence, no single reporter provides a clear picture of how auxin gradients affect transcription throughout the root. Instead of singular auxin-induced reporters, a genome-wide assessment of auxin-responsive gene expression in relation to spatial expression could be used to visualize the hypothesized meristematic auxin-response gradient in silico. This global view can be used to assess the gradient's influence on gene expression, both in the sense of its physical range and in the quantity of genes regulated. What is needed for such an analysis is a sensitive readout of the transcriptomic response to auxin in a particular tissue (e.g., the root) that can be superimposed on a spatial expression map of this tissue. Another important issue in the study of auxin in plant development is how this simple molecule can elicit so many diverse responses in different cell types (Kieffer et al, 2010). Auxin distribution is dynamic and actively changes in response to environmental and developmental cues (Grunewald and Friml, 2010). Cells will encounter varying auxin levels throughout their lifespan and their response to auxin is determined by cellular context (i.e., cell identity and spatial domain). For instance, during the formation of lateral root primordia, an increase in auxin levels leads to cell proliferation specifically in distal xylem-pole (xp) pericycle cells (De Smet et al, 2008). In contrast, in the root epidermis, higher auxin levels do not induce cell division but rather inhibit cell expansion to mediate bending of the root tip during gravitropic growth (Swarup et al, 2005). Differences in the tissue-specific expression levels of the modular auxin perception and signal transduction machinery have been suggested to predispose cells to a particular response (Weijers et al, 2005; Kieffer et al, 2010; Rademacher et al, 2011; Vernoux et al, 2011; Hayashi, 2012) (Supplementary Figure S1C; Supplementary Table S1) and it is assumed that differences in the transcriptional response to auxin lie at the basis for many of the different observed physical responses. However, the importance of cellular context on the genome-wide transcriptional auxin response is undocumented. An assessment of the response to auxin at cellular resolution is needed to begin to sort out the influence of spatial context on the transcriptional auxin response. The Arabidopsis seedling root apex is a highly amenable system for the examination of the role of auxin at a cellular resolution (Figure 1). The anatomical organization permits analysis of cell identity in the radial axis and developmental maturity in the longitudinal axis (Petricka and Benfey, 2008). Moreover, transcriptomic analyses of the individual cell types that make up this organ have provided a gene expression map of cell identities and high-resolution transcriptional data sets along the longitudinal developmental axis of the root tip (Birnbaum et al, 2003; Nawy et al, 2005; Lee et al, 2006; Levesque et al, 2006; Brady et al, 2007). Here, we conduct a genome-wide, cell type-specific analysis of auxin-induced transcriptional changes in four distinct cell populations of the Arabidopsis root. This data set is used to (1) assess the relevance of cellular context on the transcriptional response to auxin and (2) test whether this comprehensive readout of auxin responses can delineate a genome-wide auxin-response gradient. The study uncovers both broad and tissue-specific auxin-responsive transcripts, and thus provides a resource to further examine the role of auxin in a cellular context and resolve how this important hormone guides plant development and growth. This sensitive readout of auxin responses together with the previous analysis of spatial gene expression in the root was used to generate, for the first time, a view of an inclusive auxin-response gradient in the RAM. Results Auxin-regulated gene-expression analysis in distinct cell types To analyze the effect of auxin on separate spatial domains, transcriptional changes in response to auxin treatment were assayed by means of fluorescence activated cell sorting and microarray analysis of four distinct tissue-specific GFP-marker lines in Arabidopsis seedling roots. The assayed samples covered internal and external as well as proximal and distal cell populations; including marker lines for the stele, xp pericycle, epidermis and columella (Figure 2A). Roots were immersed in 5 μM indole-3-acetic acid (IAA) and treated for a total of 3 h (see Materials and methods). Expression of the markers used was stable within the treatment period (Supplementary Figure S2A). Analysis of the DII-Venus reporter under these treatment conditions showed that all tissues in the root responded to treatment within 30 min (Supplementary Figure S1A). For comparison, transcriptional responses to auxin were also assayed in intact (undigested) roots treated for 3 h. To establish that the tissue-specific expression profiles gathered here were consistent with the previously published root expression data (Birnbaum et al, 2003; Nawy et al, 2005; Lee et al, 2006; Levesque et al, 2006; Brady et al, 2007), we generated a list of cell type-specifically enriched (CTSE) genes using the public data and visualized their expression in our data set. This CTSE list was based on the expression profile template matching in a select data set of 13 non-overlapping, cell type-specific expression profiles of sorted GFP-marker lines (Supplementary Figure S2B; Supplementary Table S2). This procedure yielded a total of 3416 genes whose expression is enriched in one specific cell type (maturing xylem, developing xylem, xp pericycle, phloem-pole pericycle, phloem, phloem companion cell, quiescent center, endodermis, cortex, trichoblast, atrichoblast, lateral root cap or columella) or whose expression was enriched in two related cell types (xylem (developing and maturing xylem), pericycle (xp and phloem-pole pericycle), phloem (phloem and phloem companion cell), ground tissue (endodermis and cortex), epidermis (trichoblast and atrichoblast) or root cap (lateral root cap and columella)). The relative expression of the CTSE genes in the tissue-specific data generated in this study is differentially enriched in a manner that fits with the domains covered by the different markers used here (Supplementary Figure S2B). These results indicate a successful isolation of the transcriptomes of distinct cell types and show that the enrichment in specific tissues is consistent across the data sets. For most auxin-responsive genes in our data set, transcript levels were affected in several cell types but often showed a relatively greater response to auxin in one or more of the tissues. Two separate criteria were used to define these different levels of response (see Materials and methods for a detailed description of the statistical analysis). First, a two-way analysis of variance (ANOVA) with the factors cell type and treatment was used to categorize auxin-regulated genes and the relation of responses between the different cell types. The ANOVA (P 1.5). The number of significantly regulated genes in the stele, xp pericycle, epidermis and columella was 2059, 845, 1321 and 842, respectively (3771 unique genes; Figure 2C; Supplementary Table S2). In all, 1923 genes were found to be differentially regulated by auxin treatment in intact roots (t-test P 1.5; Supplementary Table S2). To generate a stringent list of auxin-responsive genes for the analysis of cell type-specific expression, we extracted the genes that passed the ANOVA for the treatment factor or interaction and also passed at least one of the four cell type-specific t-tests (Figure 2D), resulting in a total of 2846 auxin-responsive genes. Measured auxin responses were corroborated at two levels. First, we observed the significant regulation of known auxin-responsive genes in the cell type-specific data set. This includes significant regulation of 22 members of the Aux/IAA family of auxin co-receptors (Calderon-Villalobos et al, 2010), 14 GH3 auxin conjugases (Hagen et al, 1991), 18 SAURs (Hagen and Guilfoyle, 2002) and 7 LATERAL ORGAN BOUNDARY DOMAIN CONTAINING PROTEIN (LBD) transcription factors (Shuai et al, 2002) (Supplementary Figure S2C–F; Supplementary Table S2). Several of the responsive LBD genes that are known to be involved in lateral root initiation (Okushima et al, 2007) displayed dramatic upregulation specifically in the xp pericycle, the tissue where lateral roots originate (Supplementary Figure S2E). These results indicate the robust induction of known auxin-responsive transcripts in the four cell types sampled in this work. Second, we confirmed that tissue-specific transcript level measurements matched auxin induction patterns in transcriptional reporter lines. This included xp pericycle-specific induction of pLBD33::GUS and pTMO6::GFP (TARGET OF MONOPTEROS 6 ) as well as stele-specific induction of pATHB-8::GFP (ARABIDOPSIS THALIANA HOMEOBOX GENE 8) and ubiquitous induction of pGH3.5::GFP and pIAA5::GUS (Figure 2E–H and Supplementary Figure S3) (Kang and Dengler, 2002; Lee et al, 2006; Okushima et al, 2007; Schlereth et al, 2010). In a comparison of auxin responses in sorted cells and intact roots, genes that responded in a greater number of cell types (t-tests P 1.5) were more likely found responsive in intact roots (t-test P 1.5; Figure 2C). Moreover, genes previously associated with the gene-ontology (GO) term response to auxin stimulus are highly significantly overrepresented only in the group of 101 genes that respond in all 4 assayed tissues (20/101 genes; Fisher's exact test P=3.51e−18). In Figure 2C, the heatmap overlaid on the Venn diagram shows the gain in sensitivity for detecting cell type-specific auxin responses compared with intact roots under the same treatment. Genes found to be regulated by auxin in only one tissue show a relatively small overlap with responses in the intact root (1411, 445, 600 and 363 genes in the stele, xp pericycle, epidermis and columella, respectively). Transcripts whose response was detected in higher numbers of tissues show a relatively larger overlap with those detected in the intact root. This suggests that many cell type-specific auxin responses may not be detected in analyses performed at the organ or organismal level because localized responses are diluted among otherwise non-responsive cells. Functional analysis of cell type-specific auxin responses Using the stringent list of (2846) auxin-responsive genes, expression patterns were ordered hierarchically by pairwise correlation. A heatmap of gene regulation patterns shows how almost all auxin-responsive genes exhibited some type of spatial bias in their regulation (Figure 3A). Although genes are most often regulated in the same direction (induced or repressed) in different cell types, the response is usually stronger in a subset of samples. These findings demonstrate a pervasive tissue-specific amplitude modulation of auxin responses, and suggest that most auxin-controlled genes have context-dependent aspects to their transcriptional regulation. To dissect spatially distinct auxin responses, dominant expression patterns were extracted and used to group genes with similar responses (Supplementary Figure S4A; Orlando et al, 2009). These response clusters showed a significant overrepresentation of diverse GO terms (Supplementary Table S3). Extending the trend noted above for genes significantly regulated in all tissues, genes previously associated with the response to auxin stimulus as well as auxin mediated signaling and auxin homeostasis were mainly overrepresented in clusters containing genes with relatively uniform upregulation of expression; these included 10 Aux/IAAs and 4 GH3s (Figure 3B; Supplementary Figure S4B clusters 15 and 16; Supplementary Table S3). Four IAAs and GH3.3 were included in a cluster that showed relatively stronger induction in the stele and the induction of GH3.6/DWARF IN LIGHT 1 was strongest in the columella. Two genes previously associated with the response to auxin, LATE ELONGATING HYPOCOTYL and an uncharacterized homeodomain transcription factor (At1g74840), were found in a cluster of genes with strong downregulation in the pericycle. PIN-FORMED 7, NO VEIN and ACAULIS 5 are linked to the auxin-transport GO term found to be overrepresented in a cluster with relatively strong induction in the stele and pericycle. Genes associated with auxin biosynthesis were overrepresented in a cluster of uniformly downregulated genes. These enrichments show that, although most genes previously associated with the auxin response display broad induction, there are cell type-specific expression biases to the transcriptional regulation by auxin among genes that influence its own perception, metabolism and transport. Several auxin-response clusters representing a localized spatial pattern of induction or repression showed overrepresentation of functions linked to growth processes known to be regulated by auxin. For example, clusters of genes that showed epidermis-specific downregulation by auxin (e.g., cluster 37) had statistically overrepresented GO terms for trichoblast maturation (Figure 3C; Supplementary Figure S4; Supplementary Table S3). These clusters of genes potentially identify a large component of the transcriptome influenced by auxin signaling in the epidermis to regulate development or responses to environmental cues. Genes associated with cell wall modification and cytoskeleton modification as well as transmembrane transport and peroxidase activity were also overrepresented in this cluster, pointing to processes that may mediate auxin's specific effects on the epidermis. Promoter analysis of the cell type-specific auxin-response clusters was conducted to look for overrepresentation of the canonical auxin-response element TGTCTC (Liu et al, 1994). Clusters 15 and 16, which show relatively uniform upregulation of gene expression across tissues (Supplementary Figure S4A), contain significantly more genes with this element in the 500-bp upstream of their transcription start site than expected by chance (hypergeometric distribution analysis; Supplementary Table S3). Additionally, the occurrence of the generic TGTCNC and the individual -A-, -C- and -G- variants was examined, with the finding that TGTCAC, TGTCCC and TGTCNC were also overrepresented in the promoters of the uniformly upregulated genes assigned to dominant expression patterns 15 and 16. Furthermore, TGTCAC was overrepresented in the promoters of genes assigned to pattern 34, which shows downregulation in all tissues that is strongest in the stele (Supplementary Figure S4A). None of these elements were significantly enriched in any other upregulated or downregulated clusters. These results suggest that direct targets of auxin signaling through the auxin-response promoter element are generally uniformly induced across tissues of the root, and that variants of the canonical element may also participate in auxin regulation of transcript levels. Auxin effects on transcriptional cell identity To explore the influence of auxin on cellular development in the root in more depth, the CTSE sets of cell-identity markers (Supplementary Figure S2A; Supplementary Table S2) were used to analyze the effect of auxin on tissue-enriched genes in our cell type-specific data set. The overlap between the stringent list of 2846 auxin-responsive genes and the 3416-gene CTSE list enabled us to assess whether auxin had a positive or inhibitory overall effect on transcriptional cell identity. Among the overlapping set, genes enriched specifically in the quiescent center and developing xylem are upregulated by auxin at a significantly higher proportion than expected by chance, whereas genes enriched in maturing xylem, cortex and trichoblasts are downregulated more frequently than expected (χ2-test P 1.5 was set for the tissue-specific and intact root t-tests. To generate the stringent list of 2846 auxin responders, genes had to pass the ANOVA for treatment or interaction (P 1.5). For co-expression analysis, hierarchical clustering was performed on the stringent list of auxin responders with pairwise Pearson's correlation using gene expression lists of replicate sample averages that were row normalized (Multiple Experiment Viewer). Branch length distribution of the HCL tree and the figure of merit (FOM) of iterative K-means clustering runs were used to gauge the expected number of clusters (Multiple Experiment Viewer). A Fuzzy K-means clustering search for dominant expression patterns was executed employing the R script by Orlando and co-workers for the manipulation of large-scale Arabidopsis microarray data sets (Orlando et al, 2009). Clusters containing 0.8. Microscopy Confocal microscopy was performed with SP5 (Leica) and LSM710 (Zeis) microscopes and software. Cell walls were stained by 10 min incubation in 10 μg/ml propidium iodide (dissolved in water). GUS reporter gene lines were stained in 50 mM phosphate buffer pH 7, 0.5 mM ferricyanide, 0.5 mM ferrocyanide, 0.05% (v/v) Triton X, 1 mM X-Gluc, for 24 h at 37°C. The staining reaction was stopped and seedlings were fixed and cleared with ethanol and mounted in water. Staining was visualized with an Axioskop (Zeiss) microscope. Supplementary Material Supplementary Information Supplementary Information Supplementary Table S1 Expression of the auxin signaling components in different cell types and longitudinal sections of the Arabidopsis root Supplementary Table S2 Cell type-specific auxin responses in the Arabidopsis root Supplementary Table S3 Dominant expression patterns in cell type-specific auxin responses Supplementary Table S4 chi squared tests for ratio's of induced-to-repressed expression of cell type-specifically enriched genes Supplementary Table S5 Analysis of publicly available microarray data Review Process File
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              Crosstalk in cellular signaling: background noise or the real thing?

              During the past two decades, molecular biologists and geneticists have deconstructed intracellular signaling pathways in individual cells, revealing a great deal of crosstalk among key signaling pathways in the animal kingdom. Fewer examples have been reported in plants, which appear to integrate multiple signals on the promoters of target genes or to use gene family members to convey signal-specific output. For both plants and animals, the question now is whether the "crosstalk" is biologically relevant or simply noise in the experimental system. To minimize such noise, we suggest studying signaling pathways in the context of intact organisms with minimal perturbation from the experimenter. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                J Exp Bot
                J. Exp. Bot
                exbotj
                Journal of Experimental Botany
                Oxford University Press (UK )
                0022-0957
                1460-2431
                05 January 2018
                02 January 2018
                02 January 2018
                : 69
                : 2 , Special Issue: Recent Advances in Auxin Biology
                : 133-136
                Affiliations
                [1 ]Wageningen University & Research, Laboratory of Biochemistry, The Netherlands
                [2 ]Department of Biology, University of Washington, USA
                [3 ]Institute of Integrative Genome Biology and Department of Botany and Plant Sciences, University of California, USA
                [4 ]FAFU-UCR Joint Center for Horticultural Biology and Metabolomics Center, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, China
                Author notes
                Article
                erx463
                10.1093/jxb/erx463
                5853209
                29309681
                © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Experimental Biology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Pages: 4
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                eXtra Botany
                Special Issue Editorial

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