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 AJPS  Vol.7 No.2 , February 2016
Shade-Inducible Gene Expression Change in Arabidopsis thaliana at Different Temperatures
Abstract: We tested whether the plant response to an environmental factor could be affected by the context of another factor by using shade avoidance response at different temperatures. Depleting the red light (R; λmax = 660 nm) and/or enriching the far-red light (FR; λmax = 730 nm) results in a low R:FR ratio in the environment, which induces shade avoidance response such as elongation of petioles and reduction of plant pigments. On the other hand, warmer environmental temperature is known to mimic shade avoidance response under normal light condition, suggesting a potential crosstalk between the temperature and the light quality signals. Therefore, we investigated the patterns of gene expression responses to low R:FR ratio in different temperature contexts (22°C and 26°C) through microarray analyses. Similar, yet distinct patterns between the two responses were implicated by the levels of correlation in the commonly affected MapMan bins. However, the induction levels of typical shade genes such as ATHB2, IAA29, IAA19, HFR1, YUC8, and FT were very similar at both temperatures. Moreover, petiole length, chlorophylls, carotenoids, and anthocyanins contents did not support any statistically significant interaction between the light quality and the high temperature responses despite the obvious independent effect of each signal, which suggests cumulative effects of two independent responses. Nevertheless, other types of low R: FR-responsive genes with differential expression patterns at different temperatures were identified. They are overrepresented in secondary metabolism, lipid transport, oxidative stress, jasmonic acid, ethylene, light, pathogen defense responses, and extracellular region.

Received 5 January 2016; accepted 26 February 2016; published 29 February 2016

1. Introduction

Plant development is greatly affected by environmental factors such as light, temperature, and water. Those factors are not only important physiological components to support normal growth of a plant, but are also important signals for making decisions to turn on/off certain pathways and responses. Therefore, many studies so far have produced significant amount of information on the regulatory roles of those factors during plant development. Among those factors, light is an important factor that affects not only photosynthesis but also various stages of plant development from seed germination to morphogenesis and to flowering. All those aspects of plant development are regulated by light intensity, quality, and directionality. Light quality that can be measured by the ratio of red (R; λmax = 660 nm) to far-red (FR; λmax = 730 nm) light irradiances is an indirect measure of plant population density in surrounding area [1] . Low R:FR ratio in the environment indicates that there is less red light available for photosynthesis due to its consumption through the photosynthesis of neighboring plants and to the reflection of far-red light which is not absorbed by those plants nearby. Under this condition plants exhibit a set of reactions called shade avoidance response including elongational growth, reduction of pigments levels, and accelerated flowering [2] .

The change in R:FR ratio is sensed by the photoreceptor phytochromes. Particularly, phytochrome B (PHYB) is known to play a major role in shade avoidance response in Arabidopsis [3] . Phytochrome-interacting basic Helix-Loop-Helix (bHLH) transcription factors, PIF4, PIF5, and PIF7 (PHYTOCHROME INTERACTING FACTOR), which are normally repressed through the interaction with the light-activated PHYB, accumulate in the nucleus under low R:FR condition and activate a set of gene expression that lead to shade avoidance response [4] [5] . On the other hand, shade promotes the expression of negative regulators, PAR1, PAR2 (PHYTO- CHROME RAPIDLY REGULATED), and HFR1 (LONG HYPOCOTYL IN FAR-RED LIGHT), which bind to PIF4 and PIF5 to inhibit their DNA binding. This in turn suppresses the shade avoidance response [6] - [10] . HFR1 is degraded through COP1 (CONSTITUTIVELY PHOTOMORPHOGENIC1) and SPA (SUPPRESSOR OF PHYA-105) mediated ubiquitination in response to low R:FR light [11] [12] . Furthermore, shade avoidance response involves phytohormone signals such as auxin, brassinosteroids and gibberellins [13] [14] , forming a complicated signaling network.

On the other hand, it is known that warmer environmental temperature mimics shade avoidance response such as elongational growth under non-shade condition [15] [16] , suggesting a potential crosstalk between the temperature and the light quality signals. Although it is not clear how the non-stressful ambient temperature is perceived by plants, several cellular components are known to mediate the signal. SPATULA, a transcription factor involved in floral organogenesis, and DELLA, a repressor of the gibberellin signaling, mediate temperature dependent growth regulation [17] [18] . PIF4 and some miRNAs regulate temperature dependent induction of flowering [19] [20] . H2A.Z-nucleosome appears to be the gate keeper of the temperature dependent expression of many genes [21] .

The phenotypic similarity between the shade avoidance and warm temperature responses led to a notion of signal integration between the two. So far, one of the integration mechanisms seems to occur through the phytohormone auxin, which is required for the elongational growth during shade avoidance response as well as high temperature-induced cell elongation [15] [22] . Furthermore, the control of auxin biosynthesis and signaling by shade and high temperature is regulated by the transcription factor PIF4 and PIF7 [4] [23] - [25] . However, it is not clear how light and temperature signals interact to control the mechanism leading to this response. In order to better understand the integration process of the two signals, we compared the global gene expression patterns during the shade avoidance responses under two different temperature conditions.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

Arabidopsis thaliana ecotype Columbia was used for all experiments. Surface sterilized seeds were sown on 0.8% agar plates containing full strength Murashige and Skoog salts (pH 5.7) supplemented with 1% sucrose and kept at 4˚C for 3 days for stratification. Seeds were germinated at 22˚C under cool white fluorescent light (80 μmol/m2sec) and grown for 10 days under the same condition. Then plants were treated with either one of the following four conditions for 24 hours before the harvest for total RNA extraction. The four conditions were created by combining a light condition and a temperature condition: either with (W + FR) or without (WL) supplemental far-red light (740 nm LED, 6 μmol/m2sec) at either 22˚C or 26˚C. Those conditions were named as W+FR22˚C, WL22˚C, W+FR26˚C and WL26˚C. The R:FR ratio was ca. 0.6 with the far-red light supplementation and ca. 4 without the supplementation. For the phenotypic study, seven-day-old seedlings grown under the above mentioned standard condition were treated with either one of the six conditions indicated in the result for additional 7 days before the analysis.

2.2. RNA Isolation and Microarray Experiment

The whole seedlings were instantly frozen by pouring liquid nitrogen directly on the plate containing agar medium, and the areal part of the seedlings (approximately 100 mg) were collected by scraping with a pre-chilled spatula. The total RNA samples were prepared using TRI Reagent TM (SIGMA, St Louis, MO, USA) by following the manufacturer’s guide. The total RNAs were treated with DNase I and purified using RNeasy Mini Spin Columns (QIAGEN, Hilden, Germany). Three independent experiments were done for three replicates. The microarray experiments were carried out using Affymetrix ATH1 gene expression array by the Heflin Center for Genomic Sciences (University of Alabama, Birmingham, AL). The raw data is available at GEO in NCBI (GSE64197).

2.3. Microarray Data Analyses

The raw data were RMA-normalized by Bioconductor Affy package and MAS5 detection calls (Present/Mar- ginal/Absent) were determined independently to select the genes with significant signal intensity. After eliminating all genes that had more than three A (Absent) calls for inconsistent signal intensity among the 12 chip data, 15,128 genes were recovered. These genes were used in MapMan analysis to identify significantly responded functional gene clusters [26] . On the other hand, these 15,128 genes were further filtered by Bioconductor LIMMA package (multiple testing adjustments, FDR < 0.05) for the statistically significant difference in gene expression levels [27] [28] . An additional ad hoc filtration procedure was applied for the genes that could not pass LIMMA but consistently up- or down-regulated (1.5 fold or log2 ratio = ±0.585) in all three replicates in any of the five comparisons mentioned in the results. Genes that passed any of those two filtration methods were pooled and used for hierarchical clustering (Cluster, v. 3.0, centered Pearson correlation, average linkage method) [29] [30] . The clusters were visualized by using TreeView (v. 1.60) [30] , and the enriched GO (Gene Ontology) terms were found by using a web-based program, Functional Annotation Tool with medium classification stringency (DAVID Bioinformatics Resources 6.7, NIAID/NIH) [31] .

2.4. Pigment Extraction and Petiole Length Analysis

Chlorophylls and carotenoids were extracted by grinding 100 mg of the areal part of plants in cold 80% acetone with a mortar and a pestle. After 1 hour of incubation on ice in a dark place, the debris was pelleted by centrifugation. The absorbance (wavelength at 663.2 nm, 646.8 nm and 470 nm) of the supernatant was measured by using a spectrophotometer, and the data was analyzed as described previously [32] : Chlorophyll a = (12.25 × A663.2) − (2.79 × A646.8); Chlorophyll b = (21.5 × A646.8) − (5.1 × A663.2); Carotenoids = {(1000 × A470) − (1.82 × Chl.a) − (85.02 × Chl.b)}/198. The resulting concentrations were shown as μg/10 mg plant fresh weight. The relative amount of pigment level was shown as the percentage (%) of the amount of Chlorophyll a from the samples grown at 22˚C under white light (WL) condition.

Anthocyanin was extracted by grinding 100 mg of the areal part of plants in 1% HCl in methanol. After 1 hour of incubation on ice in a dark place, the debris was pelleted by centrifugation. The absorbance (wavelength at 530 nm and 657 nm) of the supernatant was measured by using a spectrophotometer, and the data was analyzed as described previously [33] : Anthocyanin = A530 − (0.25 × A657). The resulting concentrations were shown with arbitrary unit per 100 mg plant fresh weight. The relative amount of anthocyanin level was shown as the percentage (%) of the amount of anthocyanin from the samples grown at 22˚C under white light condition.

For the petiole length analysis, the longest petiole of each plant was collected and photographed. The lengths of petioles in the digital images were determined by using NIH Image J program [34] .

3. Results

3.1. The Microarray Experiments

To compare shade avoidance responses under different temperature contexts, we carried out a microarray gene expression study. Treatment conditions were generated by combining a temperature (22˚C or 26˚C) and a light condition (high or low R:FR ratio). The light environment with low R:FR ratio was produced by supplemental far-red LED lights (W+FR) in addition to regular white lights (WL). The combinations of them resulted in four different conditions (WL22˚C, W+FR22˚C, WL26˚C, and W+FR26˚C; Figure 1). In addition to the standard temperature (22˚C) for Arabidopsis, a higher but relatively mild temperature of 26˚C was used in order to minimize any heat-related stress responses. After eliminating all genes that had more than three Absent calls (MAS5 detection calls) among the 12 chips data (three replicates per condition), 15,128 genes were recovered. Unlike traditional microarray analyses in which only two different conditions are compared (control vs. treatment) several different comparisons of expression data are possible with four different experimental conditions (Figure 1). Each comparison was named as treatment “effect”, and a specific number is given such as “W+FR effect at 22˚C”, (comparison <1>; W+FR22˚C vs. WL22˚C). Likewise, other four “effects” were named as “W+FR effect at 26˚C” (comparison <2>; W+FR26˚C vs. WL26˚C), “high temperature (26˚C) effect under WL” (comparison <3>; WL26˚C vs. WL22˚C), “high temperature (26˚C) effect under W+FR” (comparison <4>; W+FR26˚C vs. W+FR22˚C), and “combined effect of both W+FR and high temperature (26˚C)” (comparison <5>; W+FR26˚C vs. WL22˚C). The scatter plots of average signal intensity of three replicates support the general assumption in microarray experiments that most genes do not show any significant difference in their expression levels in response to any treatments (Supplement Figure S1).

In all five treatment effects, there are not many genes that exhibited two fold (average log2Ratio = ±1) or higher expression change. Even when the cut-off value was set to 1.414 fold (average log2Ratio = ±0.5) or higher, the percentages of differentially expressed genes were as low as 0.72% (109 genes for <2> W+FR effect at 26˚C) and at most 2.01% (304 genes for <5> W+FR+26˚C effect) of 15,128 genes (Supplement Figure S2). This result suggests that our conditions were mild enough and did not overload the plants with dramatic or saturated levels of stimuli that lead to a ceiling effect which can be a problem when expecting potential additive effects. Although the RT-PCR results for several selected genes across different treatment effects confirmed the microarray data, the absolute values of the average log2Ratio from the microarray experiments were slightly lower than those of the RT-PCR results in general (microarray:RT-PCR = 0.85:1; Supplement Figure S3). Therefore, we do not rule out the possibility of reduced technical sensitivity of detection for the gene expression change, while it is not likely to affect the result of our study that tested overall tendency of the responses.

3.2. Overview of Gene Expression Patterns in Different Environmental Contexts

In order to obtain a bird’s eye view on the five different treatment “effects” mentioned above (Figure 1; <1> ~ <5>), we carried out pair wise comparisons among those “effects” using scatter plots (Figure 2). In general, the W+FR (low R:FR) effects at 22˚C and at 26˚C (<2> vs. <1>) exhibited limited levels of correlation with somewhat less prominent gene expression change at 26˚C than the one at 22˚C (Figure 2(a)). On the other hand, the high temperature (26˚C) effects under the two different light conditions (<4> vs. <3>) are relatively similar to each other (Figure 2(b)). These data suggest that the overall pattern of gene expression change in response to low R:FR is dependent on the ambient temperature, whereas response to high temperature (26˚C) treatment is relatively less affected by the ambient R:FR light ratio. Note that the levels of correlation in these comparisons

Figure 1. Microarray experimental design. The comparisons of data from different conditions were shown by arrows between the boxes. WL, white light only (high R:FR). W+FR, white light with supplemental far-red light (low R:FR). Numbers next to the arrows are the serial numbers of treatment effects used in this study (see text).

(a) (b) (c)(d) (e)

Figure 2. Comparisons among different treatment effects. The measure of treatment effect (any one of <1>. through <5> in Figure 1) on each individual gene was determine6d by the average of log2 (treated/untreated). In each scatter plot two different effects were compared. (a) Between the two W+FR effects (26˚C vs. 22˚C); (b) between the two 26˚C effects (W+FR vs. WL); (c) between the W+FR effect at 22˚C and 26˚C effect under WL; (d) between the combined effect of W+FR+26˚C and W+FR effect at 22˚C; (e) between the combined effect of W+FR+26˚C and 26˚C effect under WL. The trend line is shown in each panel in addition to a diagonal line for the hypothetical perfect correlation.

contrast with the absence of correlation between the high temperature only effect and the W+FR only effect (<3> vs. <1>; Figure 2(c)). When the combined effect of low R:FR and high temperature (<5> W+FR+26˚C effect) is compared with either of any single treatment effect such as low R:FR only (<1> W+FR effect at 22˚C) or high temperature only (<3> 26˚C effect under WL), a higher level of correlation was found with high temperature only treatment (<5> vs. <3>) and a less pronounced correlation with low R:FR only treatment (<5> vs. <1>) (Figure 2(d) and Figure 2(e)), suggesting that the high temperature has more influence than the light quality on the combined effect under this condition.

3.3. The Most Affected Gene Ontology Terms in Each Treatment Effect

To identify significantly affected functional gene clusters, we conducted MapMan analysis [26] using the 15,128 genes. First, significantly affected MapMan bins in at least one of the five different treatment effects were determined (Figure 3(a); Supplement Table S1). Again, there is a general tendency that similar treatments affect similar functional groups with less pronounced resemblance between the W+FR effects at different temperatures (<1> and <2>) than the temperature effects under different light conditions (<3> and <4>), confirming the pattern of individual gene expression as shown in the scatter plots above (Figure 2). Overall, more bins are affected by 26˚C treatments than by low R:FR light (W+FR) treatment. Next, the numbers of common MapMan bins significantly affected in two different treatment effects were identified, and the percentage of the overlapped bins to the total significant bins in each treatment effect was determined and shown with modified Venn diagrams (Figure 3(b)). Relatively higher level of overlap was observed between the two high temperature effects (<3>:<4>, 54.5% of 26˚C effect under WL and 66.7% of 26˚C effect under W+FR), whereas the number of bins responded to both W+FR effects is relatively low (<1>:<2>, 42.9% of W+FR at 22˚C and 33.3% of W+FR at

(a) (c)

Figure 3. Significantly affected MapMan bins. (a) A heat map visualizing the significantly responded MapMan bins. The brightness of color reflects p-values (Benjamini-Hochberg corrected); (b) venn diagrams showing the numbers of the overlapped (grey) and the non-overlapped (white) significant bins (p-value < 0.05); rectangular shape was used to save space. The percentages indicate the proportions of the overlapped bins to the total number of significant bins in each treatment effect; (c) the p-values of some notable bins in (a) are shown. The full list is provided in Supplement Table S1.

26˚C), confirming the limited similarity between the two W+FR treatment effects compared with the one between the two high temperature effects (Figure 2). The combined effect of W+FR and high temperature (<5> W+FR+26˚C) is similar to any of the two high temperature effects (<3> or <4>), which contrasts with lower levels of overlap with any of the W+FR effects (<1> or <2>), suggesting a stronger influence of high temperature than the low R:FR effect in the combined response. Together with the scatter plot data (Figure 2) these results suggest that there are higher levels of overlap between the similar treatment effects in terms of individual gene expression (Figure 2) as well as functional gene clusters (Figure 3(a) and Figure 3(b)).

Figure 3(c) lists some of the notable MapMan bins shown in Figure 3(a), (the full list of significant bins is provided in Supplement Table S1). It is intriguing that the supplemental far-red light treatment (W+FR) led to a slightly different pattern of response at 26˚C compared with the response at 22˚C as shown in the scatter plot and MapMan analysis (Figure 2(a) and Figure 3). For example, protein degradation family responded significantly at 22˚C whereas genes for DNA synthesis/chromatin structure are affected more at 26˚C. Also, different classes of secondary metabolism responded at different temperatures. While isoprenoids-related genes are more affected at 22˚C, more flavonoids-related genes are affected at 26˚C. Therefore, there is some level of distinction in the pattern of gene expression responses to low R:FR light treatment depending on the temperature context. In the same way, there is also some distinction in the high temperature responses under different light conditions, although the degree of similarity is higher than in the two W+FR responses.

3.4. Low R:FR Light and High Temperature Conditions Affect Different Sets of Auxin-Related Genes

The common MapMan bins responded to W+FR under both temperature conditions are photosystems, tetrapyrrole synthesis, thioredoxin, AUX/IAA family, post-translational modification, and transport (Figure 3(c); Supplement Table S1) while genes related to photosystems, auxin and jasmonate metabolism as well as protein synthesis/degradation are affected by 26˚C treatments regardless of the light condition. Notable common themes between the W+FR responsive groups and the high temperature responsive groups are “photosystems” and “auxin”. Particularly, identifying “auxin” as a common response confirms the previous notion that both low R:FR ratio and high temperature can independently trigger cell elongation via auxin synthesis and signaling [4] [23] - [25] .

However, low R:FR condition affected more of regulation of transcription (bin #27.3) including AUX/IAA genes whereas high temperature condition affected more of auxin metabolism (bin #17.2). Therefore, we dissected the expression pattern within those notable bins by interrogating and visualizing individual gene expression in those clusters (Figure 4). In general, many AUX/IAA genes, homeobox transcription factors, and indole-3-acetic acid amido synthetases (GH3s) that convert active IAA to inactive IAA compounds are mostly up-regulated by low R:FR (W+FR) but not by high temperature (bin #17.2.3, #27.3.22, #27.3.40), while IAA-amino acid conjugate hydrolases that convert inactive IAA compounds to active IAA are up-regulated mostly by high temperature but not by low R:FR (bin #17.2.1). This suggests that the mode of regulation for auxin signaling can be different between the light quality and the temperature responses under our experimental conditions.

3.5. Classification of Responsive Genes According to Gene Expression Patterns

To have a closer look at the responsive genes, we identified 484 genes that exhibited statistically significant response to any of the above mentioned five treatment effects. In addition, 27 additional, non-overlapping genes were selected that could not pass the stringent statistical test but were consistently up- or down-regulated by at least 1.5-fold in all three replicates in any of the above five treatment effects (Materials and Methods). Those 511 responsive genes were clustered based on their expression patterns by hierarchical clustering (Figure 5). Then 11 arbitrary clusters were formed by grouping the nodes with genes that exhibited similar expression patterns (Figure 5; the full list of genes for each cluster is provided in Supplement Table S2). To correlate the gene expression pattern and the function of those genes, highly enriched Gene Ontology (GO) terms in each cluster were identified by a web-based program, Functional Annotation Tool (DAVID Bioinformatics Resources 6.7, NIAID/NIH; [31] ). The genes in cluster [a] generally exhibit up-regulation upon low R:FR (W+FR) treatment at both temperatures (<1> and <2>) but are not responsive to high temperature (26˚C) under any light conditions applied (Figure 5). Again, strong enrichment of auxin response related genes were found in this cluster (Table 1). On the other hand, genes up-regulated only upon high temperature treatment regardless of the light

Figure 4. Individual gene expression patterns in auxin related MapMan bins. The expression levels of genes that belong to auxin related MapMan bins were shown in a heat map. Only those with the log2 Ratio of greater than ±0.3 in any of the five treatment effects are shown.

Table 1. Gene ontology analyses of 11 clusters. Enriched GO terms in each cluster were identified through the web-based program, Functional Annotation Tool (DAVID [31] ). BP: Biological Process, MP: Molecular Function.

(a) (b)

Figure 5. Expression patterns of the responsive genes. (a) Statistically significant responsive genes in at least one of the five comparisons were clustered using hierarchical clustering. Eleven clusters (a - k) are labeled next to the thumbnail image; (b) The numbers of the commonly responded (grey) and of the uniquely responded genes (white) (1.5 fold or higher) are shown in modified Venn diagrams for pair wise comparisons between different treatment effects. Rectangular shape was used to save space. The size of the boxes roughly corresponds to the number of responded genes in each category.

condition (<3> and <4>) are related to heat stress, oxidative stress, high light intensity, and jasmonic acid (Table 1, cluster [i]). Genes that show a down-regulation trend in all treatments (cluster [k]) are abiotic stress related, such as low temperature/osmotic stress induced genes. In clusters [b] and [c], the W+FR responsive gene expressions were dependent on the temperature and the high temperature responsive gene expressions were dependent on the light quality. Highly enriched in cluster [c] are the cell wall biogenesis related genes, but no significant GO terms were identified in cluster [b] (Figure 5; Table 1). This may be due to the small number of genes in this group (23 genes).

3.6. Shade Avoidance Response under Different Temperature Conditions

In a number of previous reports important signature genes for shade avoidance response have been revealed. We looked specifically into some of those genes in our microarray data (Table 2). Despite the overall distinct patterns of gene expression responses among the different treatments shown above, most of those genes did not show differential expression patterns in response to W+FR at two different temperatures we tested (<1> vs. <2>). Of those genes ATHB2, HFR1, IAA29 and FT are highly induced by low R:FR treatment (W+FR) as shown in many previous studies. In a different temperature context, however, the induction levels of those genes were strikingly similar. Not only the ratio of the signal intensities (Table 2) but also the actual normalized signal intensities of the microarray chips support the observation that those genes did not respond differentially at 22˚C

Table 2. Expression responses of shade induced genes. Average log2Ratio (±SD) in five different treatment effects are listed.

To investigate the consequence of the above mentioned gene expression response at the phenotypic level, we analyzed typical phenotypes under the conditions we used for this experiment (Figure 7). An additional temperature (18˚C) was used to show the trend outside the range used in this study. As expected, the supplementation of far-red light (W+FR) induced petiole elongation and reduction of pigments content at all temperatures tested. In general, those phenotypic changes were enhanced when higher ambient temperature was used. However, two-way ANOVA analyses failed to support the idea of statistically significant interaction between the two factors, low R:FR ratio and high temperature. This suggests that the phenotypic responses to low R:FR ratio are not differentially regulated at different temperature conditions, and that the enhanced responses at a higher temperature are due to additive effects of the two responses.

(a) (b) (c)(d) (e) (f)

Figure 6. Microarray signal intensities of shade responsive genes. Normalized average signal intensities of shade inducible genes under indicated conditions. Error bars indicate standard deviations of three replicates. (a) ATHB2; (b) HFR1; (c) FT; (d) IAA29; (e) IAA19; (f) YUC8.

(a) (b)(c) (d) (e) (f)

Figure 7. Phenotypic study did not support any statistically significant interaction between the two factors. (a) Representative plants grown under indicated conditions; (b) the lengths of petioles are shown as relative values (%) to the average length of WL-treated plants at 22˚C. (c)-(e) the levels of chlorophyll a, chlorophyll b and carotenoids are shown as relative values (%) to the amount of chlorophyll a in WL22˚C; (f) the levels of anthocyanins are shown as relative values (%) to the anthocyanin level in WL22˚C. All error bars indicate SE (for petiole length n = 19 plants, otherwise n = 5 - 7 independent experiments). The p-values shown are for the interaction tests between the two factors determined by two-way ANOVA using the data from 22˚C and 26˚C conditions.

3.7. Differentially Expressed Genes under Different Environmental Contexts

Although the typical shade responsive genes did not behave differently upon supplemental far-red light (W+FR) treatments at two different temperatures (Table 2; Figure 6), our cluster analysis (Figure 5) as well as the scatter plots (Figure 2(a)) indicates that there are genes differentially responded to the supplemental far-red light under different temperature conditions (<2> vs. <1>). Therefore, we searched such genes by generating log2Ratios of W+FR effects at 26˚C and at 22˚C ([W+FR effect at 26˚C]/[W+FR effect at 22˚C]) among the 15,128 genes mentioned earlier. A positive value indicates a higher level of induction at 26˚C than at 22˚C, and a negative value indicates a lower level induction at 26˚C than at 22˚C. The log2Ratios for the vast majority of the genes (14,410 or 95.3%) fell into a range between −0.3 and +0.3, meaning very similar levels of gene expression change between the two treatment effects. The genes outside of this range (718% or 4.7%) were further subdivided into four ranges: less than or equal to −0.5 [α], −0.5 - −0.3 [β], +0.3 - +0.5 [γ], and higher than +0.5 [δ] (Figure 8). Only 1% of 15,128 genes belong to the group [α] (124 genes) and the group [δ] (25 genes). Again, the statistically significant groups of genes in each range were identified through Functional Annotation Tool (DAVID Bioinformatics Resources 6.7, NIAID/NIH [31] ; Tables 3-6). Many genes that exhibited reduced levels of expression in response to low R:FR ratio at 26˚C (<2> W+FR effect at 26˚C) are involved in various processes such as secondary metabolism, lipid transport, oxidative stress, and jasmonic acid response. Many of those gene products are targeted to the extracellular region or cell wall. It is intriguing that quite a few of those genes are also involved in pathogen defense mechanisms (Group [α] and [β] in Table 3 and Table 4; Supplement Table S3). On the other hand, there are not many genes with enhanced response to low R:FR ratio at 26˚C (<2> W+FR effect at 26˚C). Pathogenesis-related thaumatin superfamily proteins in group [γ] are the only statistically significant group in this category when multiple test corrections were applied to the p-value (Table 5). Therefore, in order to find at least a tendency of this differential response, additional GO terms were identified by less stringent statistical approach without multiple test corrections (p-value < 0.02; Table 5 and Table 6). In this analysis many transcription factors that are related to pathogen defense process, light response, and ethylene signaling were found in group [γ]. At the extreme end of up regulated genes at 26˚C (group [δ]) were genes whose products are targeted to the extracellular region or cell wall, which are also related to defense mechanisms against pathogens (Table 6; Supplement Table S3).

Figure 8. Histogram showing the numbers of genes differentially responded. The frequencies of Log2 [(W+FR effect at 26˚C)/(W+FR effect at 22˚C)] among the 15,128 genes are shown.

Table 3. Functional classification of the genes in group [α]. Genes with the log transformed ratio ([<2>W+FR effect at 26˚C]/[<1>W+FR effect at 22˚C]) of less than or equal to −0.5 were analyzed by the Functional Annotation Tool (DAVID Bioinformatics Resources 6.7, NIAID/NIH [31] ). Shown are clusters with multiple test corrected p-values of 0.05 or less (Benjamini).

Table 4. Functional classification of the genes in group [β]. Genes with the log transformed ratio ([<2>W+FR effect at 26˚C]/[<1>W+FR effect at 22˚C]) of −0.5 - −0.3 were analyzed by the Functional Annotation Tool. Shown are clusters with multiple test corrected p-values of 0.05 or less (Benjamini).

Table 5. Functional classification of the genes in group [γ]. Genes with the log transformed ratio ([<2>W+FR effect at 26˚C]/[<1>W+FR effect at 22˚C]) of 0.3 - 0.5 were analyzed by the Functional Annotation Tool. Shown are clusters p-values of 0.02 or less.

Table 6. Functional classification of the genes in group [δ]. Genes with the log transformed ratio ([<2>W+FR effect at 26˚C]/[<1>W+FR effect at 22˚C]) of higher than 0.5 were analyzed by the Functional Annotation Tool. Shown are clusters p-values of 0.02 or less.

4. Discussion

Light and temperature are important environmental factors for plant development and survival. Both light and temperature can regulate various aspects of physiological process such as seed germination, flowering, plant architecture and cold tolerance. Many studies so far suggest integration of light quality and temperature signals in plants [43] . In the present study the gene expression patterns of shade avoidance response at different temperatures were investigated in order to better understand the integration process between the light quality and the temperature signals, which revealed similarities and differences in the responses in different temperature contexts. Despite the distinctions in global gene expression patterns, the most representative shade induced genes did not show any differential responses at different temperatures. On the other hand, we identified some other shade responsive genes that are differentially regulated under different temperature conditions.

4.1. Experimental Condition

4.2. The Shade Avoidance Response and the High Temperature Response

Comparing the overall gene expression responses to low R:FR light condition (W+FR) at 22˚C and to high temperature (26˚C) condition under WL confirmed the different nature of the two stimuli by showing no correlation between the two responses (Figure 2(c)). Likewise, only a small portion of the significantly responded MapMan bins exhibited an overlap between the two treatment effects (Figure 3). On the other hand, it was reported that warmer environmental temperature under non-shade condition induces phenotypic responses similar to shade avoidance response such as elongational growth through auxin biosynthesis as in shade avoidance response [15] [22] . Our phenotypic analyses also indicate that the high temperature effect is similar to the low R:FR light (W+FR) effect in terms of petiole length and pigment contents (Figure 7). Indeed, the auxin related genes were overrepresented both in W+FR effect at both temperatures and in 26˚C effect regardless of the light condition (Figure 3).

However, the auxin related MapMan bins that responded to light quality and the ones that responded to high temperature were not identical. The genes responded to supplemental far-red light were AUX/IAA genes, homeobox transcription factors, and indole-3-acetic acid amido synthetases (GH3s), whereas the high temperature mostly induced IAA-amino acid conjugate hydrolases (Figure 4). This suggests that the mode of regulation for the auxin content and the response is at least to some degree different in those responses. In addition to biosynthesis and degradation, active auxin levels are regulated by forming inactive conjugates with other compounds and by reversing the conjugation reactions through hydrolysis of some conjugates [46] . Indole-3-acetic acid amido synthetases (GH3s) conjugate auxins to amino acids to reduce the levels of active auxin [47] , whereas IAA-amino acid conjugate hydrolases increase the levels of active auxin by reversing the auxin conjugation reaction and drives cell expansion [48] [49] . Interestingly, no significant induction of well-known auxin-indu- cible genes such as Aux/IAA, GH3s (Figure 4) was detected under our high temperature condition, while induction of those genes normally occurred by low R:FR light treatment. Thus we think that our high temperature condition (26˚C) did not induce a significant level of auxin biosynthesis after 24 hr of treatment. The normalized signal intensities of microarray data also indicated that the typical shade induced genes known to be regulated by PIF4/PIF5 are not induced by our high temperature condition (Figure 6). This result seems to speak against the previous notion that high temperature increases auxin biosynthesis through a common pathway (PIF4) shared by the light quality response pathway [23] [25] . However, it may be due to potentially different kinetics of auxin biosynthesis in response to different stimuli and/or due to a relatively small temperature difference between the test and control samples (26˚C − 22˚C = 4˚C) compared with the previous PIF4 studies (28˚C − 20˚C = 8˚C [23] ; 29˚C − 22˚C = 7˚C [25] ). Nevertheless, plant phenotypes measured after a week long treatment exhibited high temperature induced petiole elongation and reduction of pigments levels as well as enhanced responses when both treatments were applied together. This may indicate a slower kinetics of PIF4 activation and auxin induction by 26˚C treatment compared with low R:FR treatment, which may eventually have led to the exhibited phenotypes. Alternatively, this may be due to the results of an accumulation of small differences over time, or even be due to a PIF4-independent process. In fact, 26˚C treatment alone could induce cell wall related genes in our study (Cluster [c] in Figure 5; Table 1). Further comparative investigation on the dynamics of shade avoidance response and of temperature response will be needed to answer this question.

4.3. The Shade Responsive Genes in the Context of Different Temperatures

The expression levels of the majority of genes (Figure 2 and Figure 8) and the comparisons of the most affected gene ontology terms (Figure 3) indicate that the gene expression changes in response to low R:FR at 22˚C and at 26˚C share similar yet distinct characteristics. On the one hand, many of the responsive genes to each stimulus are involved in the same biological processes. The overrepresented gene families at both temperatures are photosystems, tetrapyrrole synthesis, thioredoxin, AUX/IAA family, post-translational modification, and transport (Figure 3 and Figure 4). In the same way, the high temperature responses under different light conditions (WL vs. W+FR) resulted in similar gene expression changes in several common groups (Figure 2 and Figure 8), including the genes for photosystems, auxin metabolism, jasmonate metabolism as well as protein synthesis/degradation. Furthermore, we found that the induction levels of traditional shade responsive genes such as ATHB2, HFR1, FT, IAA29, IAA19, and YUC8 are not differentially affected in different temperature context (Table 2; Figure 6), suggesting that the high temperature did not affect the response patterns of those shade induced genes under our experimental condition. On the other hand, the global gene expression patterns and the MapMan analyses implied limited overlap and distinctions between the two responses (Figure 2 and Figure 3). The ratios between the two W+FR responses at different temperatures (26˚C/22˚C) indicated that there are differentially responded genes (Figure 8). The top 4.7% of genes showing differential expression are enriched in secondary metabolism, lipid transport, oxidative stress, and jasmonic acid response as well as to pathogen/defense response. The most affected compartment is cell wall or extracellular space, which is also implied by the hierarchical clustering and classification of responsive genes (cluster [c]; Figure 5; Table 1). In addition, although statistically not significant, we also found transcription factors for pathogen defense process, light response and ethylene signaling. Again, the auxin response related genes are not enriched among the differentially responded ones in the different temperature contexts. It is not known how such differential regulation of cohorts of genes under different temperature contexts is regulated.

The significant representation of defense related genes among the differentially regulated genes is intriguing. Since our experimental plants were grown under a sterile condition, it is not likely that the plants were consistently infected by pathogens in multiple independent replicates. Given the previously reported connections among temperature, light, and pathogen defense mechanisms, it is not surprising that the genes for defense responses were found differentially regulated under our experimental condition. Jasmonic acid and salicylic acid are not only related to defense mechanisms against various pathogens but also to the regulation of hyponastic growth which is induced by low light intensities [50] . On the other hand, low R:FR ratio compromises both salicylic acid- and jasmonic acid-mediated pathogen defense [51] [52] . Furthermore, high temperature also compromises defense responses [53] [54] . Therefore, our finding corroborates the notion of crosstalk or pathway sharing among light, temperature, and defense responses. To better understand the mechanisms of plant response to environmental factors in the field where multiple factors fluctuate independently, further dissection of the signaling network that integrates different pathways will be required.

5. Conclusion

Our results suggest that there are clear differences in the gene expression patterns in response to low R:FR condition at different temperatures. However, we did not detect any significantly different expression behaviors among the representative shade induced genes under the conditions we tested. Our data also indicate that there is a possibility of differential regulation in auxin content/response in warm temperature response and in shade response. Further investigation is needed to address this in more detail. Despite the similar expression patterns of shade inducible genes, we identified subsets of genes that are differentially regulated under different temperature conditions, which are overrepresented in secondary metabolism, lipid transport, oxidative stress, jasmonic acid, ethylene, light, pathogen defense responses, and extracellular region.

Acknowledgements

This work is supported by the National Science Foundation (HRD-1137497).

Supplement

Table S1. Significantly responded MapMan bins in at least one treatment effect.

(a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k)

Table S2. The expression levels of genes in each cluster. Statistically significant genes were grouped by hierarchical clustering. Eleven arbitrary clusters were formed by grouping the nodes with genes that exhibited similar expression patterns (Figure 5). Individual gene expression data for each cluster is included in separate spreadsheets.

(a) (b) (c) (d)

Table S3. The treatment effects and their ratios in group [α] [β]; [γ]; [δ] Values are the log2 transformed averages of three replicates.

Figure S1. Microarray scatter plots. The scatter plots compare the log transformed average signal intensities between the indicated conditions. <1> W+FR effect at 22˚C (W+FR22˚C vs. WL22˚C), <2> W+FR effect at 26˚C (W+FR26˚C vs. WL26˚C), <3> high temperature (26˚C) effect under WL condition (WL26˚C vs. WL22˚C), <4> high temperature effect under W+FR condition (W+FR26˚C vs. W+FR22˚C), and <5> combined effect of both W+FR and high temperature (W+FR26˚C vs. WL22˚C).

(a)(b) (c)

Figure S2. Number of genes showing different ranges of average log2Ratio. (a) Histogram. Five different treatment effects were shown with different colors; (b) Same data shown in a table format; (c) Same data shown as the percentage of 15,128 genes.

Figure S3. Real-times PCR results. The microarray results for ATHB2, HFR1, FT and IAA29 in different treatment effects were compared with the real-time PCR results. The blue line indicates the trend line. Real-time PCR: For reverse transcription reactions, 1 mg of total RNA and 0.5 mg of oligo (dT) primer were incubated at 70˚C for 10 min and chilled on ice. To this mixture, 4 ml of 5× reaction buffer, 40 units of RNasin (Promega, Madison, WI, USA), 20 mM of each dNTPs and 200 units of M-MLV reverse transcriptase (Promega) were added in a total volume of 20 ml. The reaction was incubated at 42˚C for 50 min, and then inactivated at 70˚C for 15 min. The first strand cDNAs were diluted to 100 ml, and 1 ml (1/100 of the initial amount) was used for a 40 ml real-time PCR reaction using SYBR Premix Ex Taq II (TaKaRa, Shiga, Japan) according to manufacturer’s instruction. As a housekeeping control gene EF1a was used. Following PCR primers were used: EF1a- forward, GATGAGACTTTCGTTATGATCGAC; EF1a-reverse, ATTGAAAACCATAATAAAAAGTCTCAGA; ATHB2- forward, 5’-CACAGTACTCTCAATCCGAAGCA-3’; ATHB2-reverse, 5’-AGCATCTCCGTAAGAACTCGC-3’; FT-for- ward, 5’-TGTTCCAAGTCCTAGCAACCC-3’; FT-reverse, 5’-ACACAATCTCATTGCCAAAGGT-3’; HFR1-forward, 5’-AAGTAGTGATGATGAATCGGAGGA-3’; HFR1-reverse, 5’-ATGGTCTTGTCGAGAACCGA-3’; IAA29-forward, 5’-ACCGAATATGAAGATTGCGACAG-3’; IAA29-reverse, 5’-CGAAGTAGCCAGTCACCCTC-3’.

NOTES

*Corresponding author.

#Contributed equally.

Cite this paper: B. Kim, B. , Peets, K. , S. Grant, J. , S. Hicks, J. , C. Zellous, D. and Anderson, D. (2016) Shade-Inducible Gene Expression Change in Arabidopsis thaliana at Different Temperatures. American Journal of Plant Sciences, 7, 352-423. doi: 10.4236/ajps.2016.72035.
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