Whole genome transcriptome analysis of rice seedling reveals alterations in Ca2+ ion signaling and homeostasis in response to Ca2+ deficiency

Cell Calcium 55 (2014) 155–165

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Whole genome transcriptome analysis of rice seedling reveals alterations in Ca2+ ion signaling and homeostasis in response to Ca2+ deficiency Alka Shankar a , Ashish Kumar Srivastava b , Akhilesh K. Yadav a , Manisha Sharma a , Amita Pandey a , Vaibhavi V. Raut c , Mirnal K. Das c , Penna Suprasanna b , Girdhar K. Pandey a,∗ a

Department of Plant Molecular Biology, University of Delhi South Campus, Benito Juarez Road, Dhaula Kuan, New Delhi 110021, India Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai 400085, India c Radioanalytical Chemistry Division, Bhabha Atomic Research Centre, Mumbai 400085, India b

a r t i c l e

i n f o

Article history: Received 9 November 2013 Received in revised form 18 January 2014 Accepted 13 February 2014 Available online 22 February 2014 Keywords: Ca2+ deficiency Starvation Gene expression Transcriptome analysis Signal transduction

a b s t r a c t Ca2+ is an essential inorganic macronutrient, involved in regulating major physiological processes in plants. It has been well established as a second messenger and is predominantly stored in the cell wall, endoplasmic reticulum, mitochondria and vacuoles. In the cytosol, the concentration of this ion is maintained at nano-molar range. Upon requirement, Ca2+ is released from intra-cellular as well as extracellular compartments such as organelles and cell wall. In this study, we report for the first time, a whole genome transcriptome response to short (5 D) and long (14 D) term Ca2+ starvation and restoration in rice. Our results manifest that short and long term Ca2+ starvation involves a very different response in gene expression with respect to both the number and function of genes involved. A larger number of genes were upor down-regulated after 14 D (5588 genes) than after 5 D (798 genes) of Ca2+ starvation. The functional classification of these genes indicated their connection with various metabolic pathways, ion transport, signal transduction, transcriptional regulation, and other processes related to growth and development. The results obtained here will enable to understand how changes in Ca2+ concentration or availability are interpreted into adaptive responses in plants. © 2014 Elsevier Ltd. All rights reserved.

1. Introduction It is well established that growth and productivity of plants depends on the available concentration of various minerals/ions in the soil. However, in many natural and agricultural ecosystems, the accessibility of these elements is often low, and thus, affects the plant growth and development, which can cause problem of food security world-wide. To cope with nutritional limitation, plants have evolved tightly controlled mechanisms to maintain mineral or ion homeostasis including acquisition of minerals from soil, its storage and remobilization, and also the optimization of

∗ Corresponding author. Tel.: +91 11 24113106x387; fax: +91 11 24115270. E-mail addresses: [email protected] (A. Shankar), [email protected] (A.K. Srivastava), akhilesh [email protected] (A.K. Yadav), [email protected] (M. Sharma), [email protected] (A. Pandey), [email protected] (V.V. Raut), [email protected] (M.K. Das), [email protected] (P. Suprasanna), [email protected], [email protected] (G.K. Pandey). http://dx.doi.org/10.1016/j.ceca.2014.02.011 0143-4160/© 2014 Elsevier Ltd. All rights reserved.

metabolic process by using these ions. Based on the current methods and knowledge, it is possible to modify the transport system and/or signaling pathways to provide plants new characteristics to improve their mineral nutrition rather than fertilization of soil, which is not sustainable for longer period. Ca2+ is an essential macronutrient and plant requires Ca2+ in large amounts. For normal growth and development, plants need 1–10 mM of Ca2+ supply and contain approx. 0.1–1% of dry matter [1–3]. This ion participates in a myriad of processes and affects nearly all aspects of plant growth and development such as signal transduction, metabolism of lipids, proteins, and carbohydrates, cell growth, cell wall and membrane stabilization [4–9]. Ca2+ deficiency in plants may lead to rapid death of cells in the apical meristem and a cessation of growth [1]. In tissues, Ca2+ deficiency caused cells to breakdown due to enhanced membrane permeability because Ca2+ accumulates as Ca2+ pectate in the cell wall and causes cells to adhere together. Deficiency symptoms were seen in leafy vegetables as “tipburn” or “brown heart” or “black heart” of celery, “blossom end rot” of watermelon, pepper, and tomato fruits,

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“bitter pit” of apple and “empty pod” of peanut because of immobile nature of Ca2+ from older tissue and its distribution through phloem [10]. Furthermore, in the presence of excess of Ca2+ , plants may suffer from Ca2+ toxicity which averted seed germination and reduced the plant growth rate [11]. Ca2+ inhibited leaf abscission and tissue senescence through cross-linking pectates and cementing cell walls [12–14]. Ca2+ ion represents an important signaling molecule and its concentration is balanced by the presence of ‘Ca2+ stores’ like vacuoles, endoplasmic reticulum, mitochondria, and cell wall. The cytosolic level of Ca2+ in plant cell is elicited in response to various abiotic and biotic stresses. The perturbation in cytosolic Ca2+ levels is termed as “Ca2+ signature”. In a generic Ca2+ regulated signal transduction pathway, the Ca2+ sensors or Ca2+ binding proteins sensed elevated level of Ca2+ and activate downstream kinases. Then, these kinases phosphorylate regulatory proteins such as transcription factors or transporters/channels, which regulate the gene expression or direct changes in activity of transporters/channels and leads to stress tolerance, plant adaptation, and other phenotypic responses [9,15–17]. In this study, we are investigating the physiological and transcriptomic responses of rice seedlings exposed to early and late stages of Ca2+ deficiency. Despite the fact, several transcriptomic analysis have been carried out under many different nutrients deficiencies but to best of our knowledge, none has been investigated for Ca2+ deficiency in rice or other plants. This analysis allowed the identification of a set of genes whose expression is regulated in response to low Ca2+ concentration in the growth media. The identification of Ca2+ responsive genes including signaling molecules, transporter proteins, transcription factors, key enzymes/proteins of metabolism, will provide a better understanding of the molecular mechanisms of plant responses to Ca2+ deprivation stress. 2. Materials and methods 2.1. Plant material and growth conditions Seeds of rice (Oryza sativa subsp. indica cv. IR64) were surface sterilized and grown hydroponically in growth room under the following conditions: 16 h light/8 h dark (28 ◦ C) photoperiod with 70% humidity. The hydroponic solution contained 1.14 mM NH4 NO3 , 0.258 mM NaH2 PO4 , 0.409 mM K2 SO4 , 0.798 mM CaCl2 , 1.31 mM MgSO4 , 0.06 ␮M (NH4)6 Mo7 O24 , 15 ␮M H3 BO3 , 8 ␮M MnCl2 , 0.12 ␮M CuSO4 , 0.12 ␮M ZnSO4 , 28 ␮M FeCl3 , 61 ␮M citric acid, pH 4.7 [18]. After 5 D of normal growth, some of the seedlings were transferred to nutrient solution lacking CaCl2 (−Ca2+ ). After 5 D and 14 D, Ca2+ (0.798 mM CaCl2 ) was resupplied to the plants grown in Ca2+ deficient medium for 6 h. The nutrient medium was changed at the interval of 2 D. The seedlings were then harvested and frozen in liquid nitrogen and stored at −80 ◦ C followed by RNA isolation. 2.2. Mineral content determination Seedlings were harvested after 5 and 14 D treatments and dried at 80 ◦ C for 48 h in an oven. 1 ml of concentrated HNO3 (spectroscopic grade) was added to the dried tissue. After 2 D of incubation at room temperature, the tissue was completely solubilized. Then, it was digested at 80 ◦ C temperature in a digester to vaporize acid. The volume was adjusted to a total of 1 ml using double distilled MQ. It was then filtered using a 0.2 ␮m filter (Advance Microdevices, India) followed by centrifugation at 10,000 × g for 5 min. Ion chromatography separations were performed on a commercial IC system (DX-500, Dionex, USA), equipped with a ICS-3000 quaternary gradient pump, a conductivity detector (ED40) and an

Cation Self Regenerate Suppressor (CSRS II, 4 mm) for suppressing the mobile phase background conductivity. The separator column employed was IonPac CS12A with its guard column, IonPac CG12 (Dionex Thermo Scientific, USA). Sample solutions were injected through a 50 ␮l fixed volume sample loop fitted with a six-port Rheodyne injector. Standard solutions of Na+ , K+ , Mg2+ and Ca2+ (ICP-standards, 1000 ppm) were obtained and working standard solutions were prepared by making appropriate dilution of the standard solutions. An isocratic mobile phase of 17 mM methane sulphonic acid (MSA) was used for separating the metal ions. 2.3. Measurement of biomass A total of 15 rice seedlings were collected from normal (+Ca2+ ) and Ca2+ deficient (−Ca2+ ) medium at 5 D and 14 D and weighted for fresh weight measurement. For the measurement of dry weight these seedlings were dried at 80 ◦ C for 48 h and then weighed again. Three biological replicates were used for fresh and dry weight measurement analysis and t-test (*P < 0.05, **P < 0.01) was used to analyze the statistical significance. 2.4. RNA extraction, labeling, hybridization and scanning Total RNA was extracted from whole seedlings, except seeds, using the TRIzol method (Invitrogen Inc., USA), and RNA was further purified by Nucleospin RNA clean-up columns (MachereyNagel, Germany). All the RNA samples were quantified using nanodrop ND-1000 Spectrophotometer (NanoDrop Technologies, USA) and then analyzed on denaturing MOPS agarose gel (1.2%). Also RNA integrity was assessed using RNA 6000 Nano Lab Chip on the 2100 Bioanalyzer (Agilent, Palo Alto, CA) following the manufacturer’s protocol. Total RNA purity was assessed by the NanoDrop® ND-1000 UV–Vis Spectrophotometer (Nanodrop technologies, Rockland, USA). We considered RNA to be good quality based on the rRNA 28S/18S ratios and RNA integrity number (RIN). The samples for gene expression were labeled using Agilent Quick-Amp labeling Kit (p/n5190-0442). Five hundred nanograms of control and test samples were incubated with reverse transcription mix at 40 ◦ C and converted to double stranded cDNA primed by oligodT with a T7 polymerase promoter. Synthesized double stranded cDNA were used as template for cRNA generation. cRNA was generated by in vitro transcription and the dye Cy3 CTP (Agilent) was incorporated during this step. The cDNA synthesis and in vitro transcription steps were carried out at 40 ◦ C. Labeled cRNA was cleaned up and quality assessed for yields and specific activity. The labeled cRNA samples were hybridized on to a Genotypic Technology Private Limited designed Custom Rice 8X60K Microarray (AMADID No: 031380). 600 ng of Cy3 labeled samples were fragmented and hybridized. Fragmentation of labeled cRNA and hybridization were done using the Gene Expression Hybridization kit of Agilent (Part Number 5188-5242). Hybridization was carried out in Agilent’s Surehyb Chambers at 65 ◦ C for 16 h. The hybridized slides were washed using Agilent Gene Expression wash buffers (Part No: 5188-5327) and scanned using the Agilent Microarray Scanner G2505C at 3 ␮m resolution. Data extraction from Images was done using Feature Extraction software Version 10.7 of Agilent. 2.5. Microarray data analysis Feature extracted data was analyzed using GeneSpring GX Version 11.5 software from Agilent. Normalization of the data was done in GeneSpring GX using the 75th percentile shift. Percentile shift normalization is a global normalization, where the locations of all the spot intensities in an array are adjusted. This normalization takes each column in an experiment independently, and computes the nth percentile of the expression values for this array,

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across all spots (where n has a range from 0 to 100 and n = 75 is the median). It subtracts this value from the expression value of each entity and normalized to specific control samples. Significant genes up- and down-regulated within the group of samples were identified. FDR (false discovery rate) adjusted statistical P-value was calculated using Benjamini and Hochberg algorithm. Differentially regulated genes were clustered using hierarchical clustering based on Pearson coefficient correlation algorithm to identify significant gene expression patterns (Table S1). Genes were classified based on functional categories and pathways using GeneSpringGX Software and Genotypic Biointerpreter-Biological Analysis Software. For GO annotation we used Singular Enrichment Analysis (SEA) of AgriGO with Rice MSU6.1 as reference background [19].

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were similarly resupplied with Ca2+ for 6 h after 14 D of growth on Ca2+ deficient medium as depicted in Fig. 1. Ca2+ deprived seedlings showed poor growth (Fig. 2A and B). After 14 D of growth in Ca2+ deficient medium, the seedlings showed retarded growth (only one leaf stage) as compared to the seedlings grown in Ca2+ supplemented medium (three leaf stage) (Fig. 2B). Besides, seedlings grown in Ca2+ deficient medium showed reduced shoot and root

2.6. Real-time PCR analysis The validation of gene expression pattern obtained from microarray was done by real time PCR. For this, we designed gene specific primers of 20 highly expressed genes using PRIMER EXPRESS version 2.0 (PE Applied Biosystems, USA) with default parameters. The primer sequences are listed in Table S6. Using BLAST tool of NCBI primer’s specificity was checked. First strand cDNA was prepared from 2 ␮g of DNase treated total RNA in 50 ␮l of reaction volume using high capacity cDNA Archive kit (Applied Biosystems, USA). One ␮l of the first strand cDNA reaction was used for quantitative real time PCR. KAPA SYBR FAST Master Mix (KAPABIOSYSTEMS, USA) was used to determine the expression level for the genes in ABI Prism 7000 Sequence detection System (Applied Biosystems, USA). Three biological and three technical replicates were analyzed for each treatment, and standard deviation and standard error were calculated. Actin was used for the normalization of Ct value of RNA samples. The relative expression value for each candidate gene were calculated using the CT method (Applied Biosystems, Foster City, CA, USA). 3. Results and discussion 3.1. Ca2+ deficiency affect growth of rice seedlings and ion homeostasis To investigate the molecular and physiological responses to Ca2+ deficiency, 5 D old hydroponically grown Indica variety rice IR64 seedlings were transferred to a Ca2+ deficient medium for 5 D and 14 D. The seedlings were resupplied with Ca2+ ion for 6 h after 5 D of growth on Ca2+ deficient medium. Another set of seedlings

Fig. 1. Schematic representation of the microarray experiment. Rice seeds were grown hydroponically in RGM (Rice Growth Medium). After 5 D of normal growth, rice seedlings were transferred to RGM without Ca2+ and they were resupplied with Ca2+ for 6 h after 5 D and 14 D, respectively.

Fig. 2. Morphological changes between seedling grown in normal and Ca2+ deficient medium for 5 D (A) and 14 D (B). Comparison between rice seedling shoot length, root length and leaf blade (C), fresh weight (D) and dry weight (E). Differences between mean values of treatments and controls were compared using t-tests (*P < 0.05, **P < 0.01).

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Fig. 3. Ion content analysis of rice seedlings during Ca2+ nutrient deficiency. Ca2+ (A), K+ (B), Mg2+ (C) and Na+ (D) content. Differences between mean values of treatments and controls were compared using t-tests (*P < 0.05, **P < 0.01).

growth and leaf blade height (Fig. 2C). Seedlings grown in Ca2+ deficient medium for 5 D showed 23% and 9.5% reduction in fresh weight and dry weight, respectively. The reduction in fresh and dry weight of seedlings grown in Ca2+ deficient medium was prominent after 14 D with seedlings showing 22% and 12% reduction in fresh weight and dry weight, respectively (Fig. 2D and E). However, there appeared to be no distinct phenotypic difference between seedlings grown in Ca2+ deficient medium and the seedlings resupplied with Ca2+ for 6 h. To select the appropriate time point for transcriptome analysis, we grew rice in normal RGM medium (Rice Growth Medium) for 5 D and then transferred them to Ca2+ deficient media. Thereafter, phenotype was closely observed and an apparent difference in the phenotype of Ca2+ deprived and control plants as well as in fresh weight/dry weight (biomass) was noticed only after 5 D. A very severe impairment of growth in rice seedling maintained in Ca2+ deficient media for longer period of time (i.e. 14 D) was observed. After observing growth differences of rice seedlings exposed to short-term or long-term Ca2+ deprivation, we decided to investigate gene expression profiles at 5 D and 14 D Ca2+ starvation. The time point taken is similar to the earlier reports where the authors have also observed the distinct phenotype of rice seedlings after 5 D in K+ deprived condition and used the same time point for root and whole seedlings transcriptome analysis [20,21]. In order to determine ion homeostasis under Ca2+ deficient growth conditions, some of the important cations such as Ca2+ , K+ , Na+ and Mg2+ ions concentration was estimated for all the treatments. The concentration of Ca2+ ion was lower in starvation condition compared to control i.e. Ca2+ plus condition. This was succeeded by an increase in levels of Ca2+ upon resupply at both 5 D and 14 D (Fig. 3A). We observed that in seedlings grown in Ca2+ deficient medium, the K+ ion concentration dropped by approx. 14% and 16% after both 5 D and 14 D respectively. Whereas, the levels of K+ increased at 5D and decreased at 14 D r after 6 h of resupply with Ca2+ (Fig. 3B). This result can be correlated with the low expression level of potassium ion transporters (HAK1, KUP1, KT1) observed at

14 D of Ca2+ starvation. On the other hand, Ca2+ deficiency results in slight rise in Mg2+ ion concentration after 5 D and 14 D of Ca2+ starvation (Fig. 3C). It has been known that deficiency of Ca2+ in plants affect the distribution of Mg2+ , and its concentration goes down [22,23]. In our study, we found the level of Na+ ion was decreased in Ca2+ deficient condition like K+ ion (Fig. 3D). Also, our transcriptome data revealed that 2 HKT transporters (Os02g0175000, Os06g0701700) were highly downregulated in Ca2+ deficient state, which aptly supports the above observation. Alteration in ion concentration upon Ca2+ deficiency clearly indicated the major role of this on plant ion homeostasis. 3.2. Overall features of the low Ca2+ stress responsive expression profile To analyze the expression profile of Ca2+ regulated genes in rice, 8X60K array was used for 5 D and 14 D of treatment. Differentially expressed genes (DEGs) under Ca2+ deficiency condition were identified using the criteria of twofold or more change with P value ≤ 0.05 based on three biological replicates. After filtering with FDR (Benjamini–Hochberg Correction), 798 and 5588 genes were found to be differentially expressed under 5 and 14 D of Ca2+ deficient condition, respectively (Figs. 4 and S1). Among these, 798 differentially expressed genes, 336 genes showed upregulation and 462 genes were downregulated at 5 D time point. Out of 5588 DEG, 2283 genes were upregulated and 3305 genes were downregulated at 14 D time point. The probe set Ids, signal intensity value, Pvalue, fold change and regulation of 336, 462 (5 D) and 2283, 3305 (14 D) genes are listed in detail in Tables S2–S5, respectively. We found that, the numbers of DEGs increased as the Ca2+ deprivation period prolonged from 5 D to 14 D and at both the stages there were more downregulated genes as compared to upregulated. This result suggests that many genes participated in restricted growth rate of rice seedlings and adaptation to Ca2+ deficient condition. Besides, in both 5 D and 14 D Ca2+ deficient conditions, 156 and 249 genes were found to be commonly up- and down-regulated.

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Fig. 4. Venn diagram showing the number of significantly differentially expressed up-regulated (A) or down-regulated (B) genes in both 5 D and 14 D of Ca2+ deficiency. The genes upregulated and downregulated at least more than twofold were selected for the analysis.

Also, K-means cluster analysis was done to determine the genes, which were involved in a common pathway or share parallel function. The analysis was carried out for significantly expressed genes found in both 5 D and 14 D of Ca2+ starvation (Fig. S2). In total 3 clusters were made from both the time-points on the basis of gene expression. Cluster 1 comprised 336 and 2283 genes from 5 D and 14 D, respectively and showed very high expression in Ca2+ deficient condition (−Ca2+ ). 365 and 427 genes from cluster 2 and 97 and 2887 from cluster 3 exhibited lower expression under Ca2+ deficient conditions (−Ca2+ ). To validate the expression profiles observed by microarray analysis in this experiment, Q-RT-PCR was performed for the 20 genes. Gene expression profiles obtained from the quantitative RT-PCR exhibited a high degree of similarity, thus confirming the reliability and robustness of the microarray data (Fig. S3). The original microarray data set has been deposited in NCBI’s Gene Expression Omnibus with the accession number GSE 50917.

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5 D and 14 D (Fig. 5). For molecular function, the most significant enrichment was observed among the various genes related to binding and catalytic activity followed by transcription regulator activity, transporter activity. Under biological processes, significant numbers of the DEGs were allocated to the metabolic processes category, followed by cellular processes, biological regulation, localization, response to stimulus, and signaling. For cellular components, DEGs were found to be involved in the cell structure. These included genes involved in the plasma membrane and external encapsulating structures such as the cell wall and cell envelope. To get an insight into the biological processes affected in Ca2+ deficit conditions in plants, it is cogent to categorize the DEGs into the biological pathways. So, we matched the differentially expressed genes (from both 5 D and 14 D) in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. This analysis clearly showed that a significant number of DEGs featured in different metabolic processes, indicating that Ca2+ deficiency severely compromise metabolic pathways. The metabolic pathways compromised in Ca2+ deficient conditions ranged from biosynthesis of secondary metabolites, carbohydrate metabolism, lipid metabolism, or amino acid metabolism. The other pathways affected include betanidin degradation, fermentation, biosynthesis of plant hormone, etc. (Fig. 6). Deficiency of a nutrient is known to prominently affect a number of metabolic pathways [21,24–26]. Prolonging deficiency of the nutrient (Ca2+ in this case) in the growth conditions leads to a higher number of genes from 5 D to 14 D belonging to the respective pathways. This kind of profile has also been observed under other nutrient deficiency from short term to long term, suggesting a global overhauling of gene expression of various pathways under prolonged exposure of nutrient deficiency and point toward complexity in the plant response to Ca2+ deprivation conditions [27–30].

3.3. Functional classification of differentially expressed genes 3.4. Differentially expressed genes encoding metabolic enzymes In order to classify the DEG based on functional annotation i.e. molecular functions, cellular components, and biological processes, GO (gene ontology) enrichment analysis was performed using the AgriGO database under low Ca2+ stress conditions after

A large number of differentially expressing genes were found to be involved in the primary metabolic processes (Fig. 5). We found 14 DEGs from 5 D and 159 DEGs from 14 D were related to

Fig. 5. A bar plot showing the AgriGO functional assignments in three GO categories i.e. cellular component, biological process and molecular function.

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Fig. 6. Metabolic pathway analysis of the differentially expressed genes using KEGG database.

carbohydrate metabolism. Similarly 35 DEGs and 144 DEGs were found to be involved in phosphate metabolism, 43 DEGs and 277 DEGs were related to nitrogen compound metabolism, 8 DEGs and 70 DEGs were related to lipid metabolism (Fig. 7A and B). In this study, we found that six rice alpha amylases (Os08g0473900, Os08g0473600, Os02g0765400, Os09g0457400, Os04g0526600,

and Os03g0661600) were significantly upregulated after 14 D of Ca2+ deficiency. Several reports have established the role of Ca2+ in metabolic processes. Ca2+ deficiency greatly affects the distribution of carbohydrate in the tissues, and an increase in the level of storage carbohydrate leads to a significant growth retardation in plants

Fig. 7. Detailed classification of metabolic process and cation binding process related genes showing transcriptional changes at (A) 5 D and (B) 14 D of Ca2+ deficiency.

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[31]. It has been reported that barley alpha amylase AMY1 and AMY2 has higher affinity for Ca2+ ions and affect starch hydrolysis [32]. The regulation of NADH dehydrogenase enzyme activity via Ca2+ ion was well established in case of mitochondrial metabolism [33]. It is well understood that Ca2+ plays a crucial role in maintaining the structural rigidity of the cell wall [34]. In our study, we found substantial number of genes like pectinesterase, pectin lyase, expansin, peroxidases, and xyloglucan fucosyltransferase were differentially expressed in both 5 D and 14 D of Ca2+ deficient condition, which clearly indicates the role of Ca2+ in cell wall synthesis/modification. Both the accumulation and the synthesis of nitrogen substances were inhibited by the Ca2+ deficiency [35]. Interestingly, 50 genes related to photosynthesis were found to be specifically downregulated, after 14 D of Ca2+ deficiency. It has been reported that Ca2+ deficiency damage chloroplast lamellae and also reduces the rates of photosynthesis in isolated chloroplasts and leaves [36–38]. Interestingly, in our transcriptomic analysis, expression of most of these genes was restored upon resupply of Ca2+ for 6 h and also the number of genes related to photosynthesis increased in 14 D of deficiency. Taken together, these results suggested that long term Ca2+ deficiency might affect the metabolic regulation of plants, which leads to very poor plant growth as reflected in the Fig. 2A and B. 3.5. Differentially expressed genes encoding cation binding proteins Gene ontology (GO) analysis clearly showed that next significantly altered category after metabolic processes was binding category. Among this binding category, we are emphasizing on the cation binding proteins, which includes zinc, iron, Ca2+ and magnesium binding proteins in 5 D of Ca2+ deficiency conditions and besides the above mentioned four cation, two new sub-categories manganese and copper binding proteins were prominently noticed after 14 D of growth in Ca2+ deficient medium (Fig. 7A and B). The category of iron binding protein includes genes encoding cytochrome P450 and peroxidase. Cytochrome P450 and peroxidase (POX) both are heme containing protein. P450s play critical roles in the synthesis of lignins, UV protectants, pigments, defense compounds, fatty acids, hormones, and signaling molecules [39]. Studies on functional characterization of POXs protein suggested a myriad of role including lignification, suberization, cross-linking of cell wall structural proteins, auxin catabolism, salt tolerance, senescence and defense against pathogens [40–45]. The plant POXs have also been implicated in the generation of ROS (Reactive Oxygen Species), which has been well reported as an important signaling molecule involved in many physiological stimuli and Ca2+ signal generation in plant under stresses [46–48]. Zinc finger family protein majorly binds to zinc ion while metabolic enzyme pyruvate kinase binds to magnesium and cupin domain containing protein binds to manganese. 19 and 40 Ca2+ binding proteins were identified in 5 D and 14 D of Ca2+ deficient condition, respectively, which largely included EF-hand family proteins, OsWAK receptor-like protein kinases, CaM, annexin, and phospholipase D. All of the above mentioned Ca2+ binding proteins have been reported as important components of Ca2+ signaling pathways [49,50]. 3.6. Effect of Ca2+ deficiency on plant ionome homeostasis Homeostasis is the tendency of a cell or an organism to maintain internal stable state, in response to any environmental stimulus. When plants are exposed to nutrition deficiency, the kinetic steady states of many ion transporters such as K+ , Ca2+ , Na+ are altered. So, it is vital for the plant to restore cellular ion homeostasis

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for metabolic functioning and growth to adapt against the ion deficient situation. Ca2+ starvation had a great impact on plant ionome and noticed by arrested growth of rice seedlings (Fig. 1A–E). Plants grown in Ca2+ deficient medium showed fluctuation in concentrations of a number of other elements like potassium, sodium, and Ca2+ itself (Fig. 3A–D). In Arabidopsis and rice, it has been well established that many transporters are involved in metal ion homeostasis [51,52]. The Ca2+ deficiency response activated the variability of other ion concentration, which in turn triggers the expression of genes encoding these ion transporters in order to alter the root uptake capacity [53–55]. Besides Ca2+ transporters (ATPase, GLR, CHX), Ca2+ deficiency influenced the potassium, sodium, nitrate, phosphate, sulphate and other transporters such as heavy metal transporters, aquaporin, ABC transporters, peptide transporter, sugar transporters and many more (Table S8). The inward K+ channel KAT1, in the plasma membrane of guard cells, which are responsible for K+ influx, are also inhibited by higher cytosolic Ca2+ [56]. These transporters might possibly play a role in the ionomic alteration upon Ca2+ depletion. The function of aquaporin was also regulated by Ca2+ in response to environmental factor [57]. For the activities of many cytosolic enzymes, and for maintaining membrane potential and osmotic pressure, intracellular K+ and Na+ homeostasis is important. Under salt stress, the maintenance of K+ and Na+ homeostasis is crucial because of Na+ toxicity. So, plants regulate cation transporters at the tonoplast and plasma membranes to maintain ion homeostasis. The SOS3/CBL4SOS2/CIPK24 (Ca2+ -binding protein) pathway has been shown to be involved in facilitating salt tolerance by regulating efflux of Na+ out of the cell by plasma membrane Na+ /H+ antiporter [58–60]. 3.7. Expression of genes that encodes Ca2+ signaling components The central dogma of Ca2+ signaling is comprised of mainly three steps i.e. generation of Ca2+ signature, recognition of the Ca2+ signature, transduction, and finally inception of a response against a particular stimulus. The cytoplasmic Ca2+ levels are highly dynamic and are regulated in response to various biotic and abiotic signals by channels, pumps and transporters [61,62]. The changes in free Ca2+ level during signal transduction are detected by Ca2+ sensor proteins [15,16]. Ca2+ dependent transcriptional regulation mechanisms involve numerous signal transducers including Ca2+ binding proteins including members of EF-hand superfamily, calmodulin (CaM) and calcineurin B-like (CBL), and Ca2+ dependent protein kinases (CDPKs) indirectly or directly regulate transcription through phosphorylation/dephosphorylation of transcription factors in response to Ca2+ increase in the cell [17]. In our transcriptomic analysis, the differentially expressing genes in Ca2+ deficient condition can be broadly catogarized into three major groups i.e. Ca2+ relay/signaling components, transporters, and transcription factors (Fig. 8 and Table S7). The first group, Ca2+ relay/signaling components includes EF-hand containing proteins, CaM like proteins (CML), CaMBP (Calmodulin Binding Protein), CIPK (CBL-Interacting Protein Kinase), CDPK (Ca2+ Dependent Protein Kinase) and annexin. Interestingly, the microarray data points toward the involvement of EF-hand proteins as early as 5 D of Ca2+ deficient condition. With 2 EF-hand containing proteins showing upregulation and 3 showing downregulation. 5 CMLs were also downregulated at early stage of deficiency. 8 EF-hands, 2 annexins, 3 CaMBPs were downregulated whereas 5 EF-hands, 12 CaMBPs, 4 CIPKs and 2 CDPKs were upregulated specifically at 14 D of Ca2+ deficiency. Calmodulin is a small protein with two pairs of Ca2+ binding sites, i.e. 4 EF-hands [63,64]. Ca2+ binding modifies the CaM closed structure into an open conformation, which facilitates

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Fig. 8. Schematic diagram of the differentially expressed genes in 5 and 14 D related to Ca2+ ion signaling, transport and transduction.

binding to target proteins. Furthermore, the expression of CaMs and CMLs was known to be induced by touch, cold, heat shock or salinity [64,65]. Ca2+ played an important role in regulating several stress mediated signaling pathways in plants by using the CBL-CIPK module [15,16,66,67]. Mechanistically, two major signaling pathway comprised of CBL-CIPK network for regulating the salt stress tolerance and low-potassium uptake and nutrition (CBL1/CBL9CIPK23-AKT1) are extensively studied Ca2+ signaling pathway in plants [68–70]. Ca2+ sensor CDPKs were identified only in plants and protists, and have an autoregulatory domain for the binding to Ca2+ ions. For regulation of CDPKs activities not only Ca2+ ions but also specific phospholipids and autophosphorylation are required [15,71]. The involvement of several of the differentially expressed genes related to CaM, CBL, CIPK and CDPKs suggest that a diverse array of Ca2+ signaling decoding components are activated during Ca2+ deficiency condition to enable plants to generate the adaptive response. At 5 D of Ca2+ deficiency, one GLR (glutamate receptor) and one CHX (cation/H+ exchanger) were upregulated while two ATPases including Ca2+ ATPase (ACA) and plasma membrane associated ATPase (AHA) were downregulated. 1 GLR, 1 CHX and 1 ATPase were upregulated while 1 CAX (Ca2+ exchanger), 2 ATPase, 2 GLR and 1 TPC (Two Pore Channel) showed downregulation after 14 D of Ca2+ deficiency (Fig. 8 and Table S8). The glutamate receptor (GLR3.3) is non-selective cation channels and facilitates Ca2+ entry into the cytosol [72]. Also, it was reported that GLR3.3 showed hypersensitivity to Na+ and K+ ions and play a crucial role in Ca2+ mediated adaptation to ionic stresses [73]. CHX proteins facilitate transmembrane movement of monovalent cations driven by the proton motive force. The transcriptome analysis of root transporters in response to cation starvation stress revealed that CHX17 shows enhanced level of expression in Ca2+ deficient condition in Arabidopsis [74]. Also, the transcript level of AtCHX17 was increased in response to high salt or abscisic acid and affects K+ uptake [75]. Plant Ca2+ ATPases are members of P-type ATPase superfamily and involved in the restoration and maintenance of ion homeostasis by pumping Ca2+ ions out of the cytosol [76]. Cation/H+ exchangers (CAX) are the major Ca2+ facilitator superfamily and predicted to localize to membrane or vacuole [77]. The transcript level of CAX2 in Arabidopsis was significantly decreased in Ca2+ starvation condition [74]. So, it was predicted that CAX2 is a vascular Ca2+ exchanger and its downregulation was related to low concentration of Ca2+ in plants in starvation state. OsTPC1 is a voltage-gated Ca2+ permeable channel, localized in the plasma membrane and has been proposed

to play important role in Ca2+ influx and regulation of growth and development in rice [78,79]. Our microarray results showed that 58 and 218 genes encoding transcription factors were differentially expressed under 5 D and 14 D of Ca2+ deficiency, respectively (Table S9). Out of 58 genes, 5 zinc finger and 3 WRKY showed upregulation while 5 DREB, 5 zinc finger (ZF), 4 MYB, 3 AP2-domain containing protein, 3 ERF, 3 HLH, and 2 WRKY were downregulated. Among late responsive genes 15 Zinc fingers (ZF), 7 MYB, 6 MADS, 6 ERF, 6 WRKY, 5 AP2- domain containing protein, 3 HLH were upregulated and reverse expression pattern was observed for 18 ZF, 15 HLH, 14 MYB, 5 DREB, 4 WRKY, 3 AP2 domain containing protein (Fig. 8 and Table S9). Ca2+ dependent transcriptional regulation mechanisms involve various signal transducers including Ca2+ binding proteins. Transcription factors like DREB1A and AP2-domain transcription factor (EREBP) were highly upregulated (105- and 83-fold), which directly link the role of Ca2+ with drought stress as well as with other abiotic stresses. Both of these transcription factors were reported to be involved in drought and low temperature signal transduction pathways [80]. The promoters of DREB1B and DREB1C were shown to bind CAMTA1 (Calmodulin Binding Transcription Activator 1) in vitro [81]. The WRKY protein family (74 members in Arabidopsis), WRKY TF’s have a characteristic DNA binding domain containing an almost invariant WRKY motif and an atypical zinc finger motif, play an important role in plant defense mechanism. It has been reported that AtWRKY7 interacts with CaM in a Ca2+ dependent manner. Moreover, AtWRKY7 is a member of WRKYIId subfamily and all the members of this family (WRKY11, WRKY15, WRKY17, WRKY21, WRKY39, and WRKY74) bind to CaM [82]. Coimmunoprecipitation assays confirmed the interaction, between WRKY43 and WRKY53 and CaM [83]. MYB transcription factor family participate in plant responses to stress [84]. Gm-CaM4, a soybean CaM mediated Ca2+ signaling response by activating an R2R3MYB2 TF [85]. Ca2+ -binding At-NIG1 (NaCl-induced gene), encodes a bHLH-type transcription factor and salt-induced gene [86]. Using high-density protein microarrays and fluorescently labeled CaMs and CMLs, revealed that a large number of Ca2+ binding proteins including different transcription factors like MADS-box family proteins (AGL1, AGL3, and AGL8), bZIP TFs (GBF1 and ABF2), MYB TFs (MYB14 and MYB70), WRKYs, Scarecrow-like TFs (SCL4), NAM TFs, and auxin related TFs (IAA31 and SAUR B) might be functioning as Ca2+ signaling components [83].

3.8. Cis-regulatory element identification and analysis of Ca2+ nutrient responsive genes Transcriptional regulation of gene expression in a network is mediated by cis-regulatory elements and their interacting transcription factors. Transcriptome analysis using microarray technology can help to identify groups of co-expressed genes under stress condition. We considered 1-kb upstream promoter sequences of 20 highly expressed (up and down) genes under Ca2+ deficient condition, which are located at different positions on chromosomes. Information about the genes and their annotation, description and expression values are listed in Table S10. In all the genes, we found at least more than two known cis-element like ABRERATCAL, DRECRTCOREAT, SITEIIATCYTC, and E2FCONSENSUS specific for Ca2+ responsiveness were presented along with many common elements including ABRELATERD1, ARR1AT, CAATBOX1, DOFCOREZM, CACTFTPPCA1, GATABOX, GT1CONSENSUS, POLLEN1LELAT52, TAAAGSTKST1, MYBCORE, WRKY71OS, etc. ABRE-related sequence or ABRE was discovered by using reporter assays to be induced in response to Ca2+ [87]. Similarly, it was shown that C-Repeat/Drought-Responsive Element, Site II, ABRE and CAM box were present in Ca2+ regulated promoter

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[88]. Among these Ca2+ responsive elements, CRT/DRE was a cold and drought-responsive element while ABRE was abscisic acid response element [89]. Site II motif was reported to be involved in mainly cell cycle control, growth, and development [90]. Therefore, the occurrence of these cis-regulatory elements in the promoter sequences of Ca2+ responsive genes might be related to several other stresses (abiotic/biotic stress), which can changes the regulation of signal transduction components to enable plants to adapt to a wide range of conditions. However, further investigations are required to elucidate the relevance of the presence of these cis-regulatory elements on the promoters of differentially expressing genes and their interaction with transcription factors to regulate the gene expression under Ca2+ deficient and other stress conditions. 3.9. Comparative analysis of Ca2+ and other nutrient deprivation with rice and Arabidopsis Since the whole genome transcriptome data is not available for Ca2+ deficient conditions in any other plant, we compare our data with other nutrient deficient (N, P, K) transcriptome data from rice as well as Arabidopsis. This kind of analysis provide insight on specific and common regulatory gene(s) or networks operating in both the model plants under a particular or other nutrient deprivation condition. To analyze the transcriptomic differences, genes showing fold change of ≥2 with P-value ≤ 0.05 in all the nutrient deficient conditions were compared in AgriGo database. Here, we compared the DEGs involved majorly in metabolism, cation binding, transcription factors, transporters and signaling components (Fig. S4). Generally, for all the conditions similar response pattern was observed in rice and Arabidopsis both i.e. metabolism category showed maximum number followed by cation binding, transcription factors, transporters and signal transduction. Also the DEGs from 14 D of Ca2+ deficiency exhibited highest number among all the nutrient deficient conditions. This result signifies that as the period of deficiency prolonged the number of differentially expressed genes increased to cope-up the plants from stressed situation. A very parallel kind of observation was also found in comparative transcriptome analysis between rice and Arabidopsis for K+ deprivation condition [20,21]. Moreover, this kind of analysis also indicates the vital role of these DEGs in nutrition deficient stress signaling management and plant development across different plant species. 3.10. Conclusion Global transcriptional profiling revealed that deficiency of one element or ion repeatedly involves modification of the expression of genes coding for proteins specific for the homeostasis of others elements, varying from uptake of ions through transporters, internal distribution via transporters and proteins that take part in assimilation of these elements. Our study emphasizes mainly the ionic signaling and their adjustments coupled with adaptation to the stress of nutrient deficiency. Ca2+ nutrition impacts a number of signaling and physiological processes and we expect that the transcriptional changes in these diverse physiological and signaling pathways are critical for adaptive responses to plant Ca2+ deficient condition. Ca2+ has emerged as an essential second messenger which mediates responses to developmental and stress stimuli in plants. Some of the Ca2+ channels/transporters, TFs, and signaling component have been identified at the molecular level but their specific roles in generating Ca2+ signals in response to stress remain to be elucidated. Future investigation of these differentially expressed genes in-planta by genetic and biochemical approaches will provide insights into the

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systematic regulation of these genes during Ca2+ deficiency stress conditions. Conflict of interest The authors declare no conflict of interest. Acknowledgements We are thankful to Genotypic Technology Pvt. Ltd., Bangalore, India for the microarray processing and data analysis reported in this publication. The research work in GKP’s lab is supported by Department of Biotechnology (DBT), Ministry of Science and Technology, India. AS and AKY acknowledge Council for Scientific and Industrial Research (CSIR), INDIA for their research fellowships. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ceca.2014.02.011. References [1] E. Epstein, Mineral Nutrition of Plants: Principles and Perspectives, Wiley, New York, 1972. [2] D.T. Clarkson, J.B. Hanson, The mineral nutrition of plants, Annu. Rev. Plant Physiol. 31 (1980) 239–298. [3] P.J. White, The pathways of calcium movement to the xylem, J. Exp. Bot. 52 (2001) 891–899. [4] H.M. Harrington, S.L. Berry, R.R. Henke, Amino acid transport into cultured tobacco cells: II. Effect of calcium, Plant Physiol. 67 (1981) 379–384. [5] H. Marschner, Mineral Nutrition of Higher Plants, 2nd ed., Academic Press, London, 1995. [6] J.F. Harper, G. Breton, A. Harmon, Decoding Ca2+ signals through plant protein kinases, Annu. Rev. Plant Biol. 55 (2004) 263–288. [7] K.D. Hirschi, The calcium conundrum. Both versatile nutrient and specific signal, Plant Physiol. 136 (2004) 2438–2442. [8] V.S. Reddy, A.S. Reddy, Proteomics of calcium-signaling components in plants, Phytochemistry 65 (2004) 1745–1776. [9] N. Tuteja, S. Mahajan, Calcium signaling network in plants: an overview, Plant Signal. Behav. 2 (2007) 79–85. [10] C.B. Shear, Calcium-related disorders of fruit and vegetables, Hortic. Sci. 10 (1975) 361–365. [11] P.J. White, M.R. Broadley, Calcium in plants, Ann. Bot. 92 (2003) 487–511. [12] B.W. Poovaiah, A.C. Leopold, Inhibition of abscission by calcium, Plant Physiol. 51 (1973) 848–851. [13] B.W. Poovaiah, A.C. Leopold, Deferral of leaf senescence with calcium, Plant Physiol. 52 (1973) 236–239. [14] B.W. Poovaiah, A.C. Leopold, Effects of inorganic salts on tissue permeability, Plant Physiol. 58 (1976) 182–185. [15] S. Luan, Protein phosphatases in plants, Annu. Rev. Plant Biol. 54 (2003) 63–92. [16] G.K. Pandey, Emergence of a novel calcium signaling pathway in plants: CBLCIPK signaling network, Physiol. Mol. Biol. Plants 14 (2008) 51–68. [17] R. Das, G.K. Pandey, Expressional analysis and role of calcium regulated kinases in abiotic stress signaling, Curr. Genomics 11 (2010) 2–13. [18] S. Yoshida, D.A. Forno, J.H. Cook, K.A. Gomez, Laboratory Manual for Physiological Studies of Rice, 3rd ed., International Rice Research Institute, Los Banos, Philippines, 1976. [19] Z. Du, X. Zhou, Y. Ling, Z. Zhang, Z. Su, agriGO: a GO analysis toolkit for the agricultural community, Nucleic Acids Res. 38 (2010) 64–70. [20] T.L. Ma, W.H. Wu, Y. Wang, Transcriptome analysis of rice root responses to potassium deficiency, BMC Plant Biol. 12 (2012) 161. [21] A. Shankar, A. Singh, P. Kanwar, et al., Gene expression analysis of rice seedling under potassium deprivation reveals major changes in metabolism and signaling components, PLoS ONE 8 (2013) e70321. [22] J.J. Rios, S.O. Lochlainn, J. Devonshire, et al., Distribution of calcium (Ca) and magnesium (Mg) in the leaves of Brassica rapa under varying exogenous Ca and Mg supply, Ann. Bot. 109 (2011) 1081–1089. [23] H. Lenz, V. Dombinov, J. Dreistein, M.R. Reinhard, M. Gebert, V. Knoop, Magnesium deficiency phenotypes upon multiple knockout of Arabidopsis thaliana MRS2 clade B genes can be ameliorated by concomitantly reduced calcium supply, Plant Cell Physiol. 54 (2012) 1118–1131. [24] J. Wasaki, T. Shinano, K. Onishi, et al., Transcriptomic analysis indicates putative metabolic changes caused by manipulation of phosphorus availability in rice leaves, J. Exp. Bot. 57 (2006) 2049–2059.

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