Notice: Wiley Online Library will be unavailable on Saturday 27th February from 09:00-14:00 GMT / 04:00-09:00 EST / 17:00-22:00 SGT for essential maintenance. Apologies for the inconvenience.
•MicroRNAs (miRNAs) play a pivotal role in post-transcriptional regulation of gene expression in plants. Information on miRNAs in legumes is as yet scarce. This work investigates miRNAs in an agronomically important legume, common bean (Phaseolus vulgaris).
•A hybridization approach employing miRNA macroarrays – printed with oligonucleotides complementary to 68 known miRNAs – was used to detect miRNAs in the leaves, roots and nodules of control and nutrient-stressed (phosphorus, nitrogen, or iron deficiency; acidic pH; and manganese toxicity) common bean plants.
•Thirty-three miRNAs were expressed in control plants and another five were only expressed under stress conditions. The miRNA expression ratios (stress:control) were evaluated using principal component and hierarchical cluster analyses. A group of miRNAs responded to nearly all stresses in the three organs analyzed. Other miRNAs showed organ-specific responses. Most of the nodule-responsive miRNAs showed up-regulation. miRNA blot expression analysis confirmed the macroarray results. Novel miRNA target genes were proposed for common bean and the expression of selected targets was evaluated by quantitative reverse transcriptase–polymerase chain reaction.
•In addition to the detection of previously reported stress-responsive miRNAs, we discovered novel common bean stress-responsive miRNAs, for manganese toxicity. Our data provide a foundation for evaluating the individual roles of miRNAs in common bean.
If you can't find a tool you're looking for, please click the link at the top of the page to "Go to old article view". Alternatively, view our Knowledge Base articles for additional help. Your feedback is important to us, so please let us know if you have comments or ideas for improvement.
Non-protein-coding RNAs (npcRNA) are a class of riboregulators that play pivotal roles in post-transcriptional regulation of gene expression in plants. MicroRNAs (miRNAs) are 21-nt-long npcRNAs that regulate gene expression through translational inhibition or target gene transcript cleavage. The latter, most extensively studied mechanism of action for plant miRNAs operates through the recruitment of a miRNA-containing effector complex (the RNA-induced silencing complex (RISC)) to its target mRNA by base-pairing complementarity. Some 29 miRNA families are conserved among flowering plants and have functions in plant development, stress responses or miRNA autoregulation. In addition, recent reports indicate that miRNAs can be organ-, species-, physiological event-, or stress-specific (Bonnet et al., 2006; Jones-Rhoades et al., 2006; Mallory & Vaucheret, 2006; Sunkar et al., 2007; Chuck et al., 2008a; Covarrubias & Reyes, 2009; Voinnet, 2009).
miRNAs that respond to abiotic stress may have relevant roles in the complex regulatory mechanisms that allow plants to cope with adverse environmental conditions. For example, miR399, which regulates the expression of ubiquitin E2 conjugase (UBC4 or PHO2), is essential for phosphorus (P) homeostasis in plants under P starvation (Bari et al., 2006; Chiou et al., 2006; Valdés-López et al., 2008). Recently, deep sequencing and reverse transcriptase–polymerase chain reaction (RT-PCR) approaches have revealed additional P starvation-responsive miRNAs in Arabidopsis (Hsieh et al., 2009; Pant et al., 2009). These studies reported the induced expression of miR156, miR399, miR778, miR827, miR2111, and miR399* during P starvation, while the expression of miR169, miR395, and miR398 was found to be repressed. Similarly, miR397, miR398, miR408, and miR857 responded to copper (Cu) concentrations and have been proposed to be involved in Cu homeostasis under conditions of Cu deficiency, through the regulation of Cu:zinc superoxide dismutase (CSD1 and CSD2), plantacyanin and various laccases (Abdel-Ghany & Pilon, 2008; Yamasaki et al., 2008). In addition, miR395, which regulates ATP sulphurylase (APS4) and a sulfate transporter (AST68), has a relevant role in sulfur (S) homeostasis during S limitation (Kawashima et al., 2009). miR167 is associated with lateral root outgrowth in response to nitrogen (N) limitation (Gifford et al., 2008). Pant et al. (2009) have reported the repression of miR169 and miR398a upon N limitation, whereas during P limitation miR778, miR827, and miR399 were induced.
The Fabaceae (legume) family comprises approximately 700 genera with > 18 000 species (Doyle & Luckow, 2003). Legumes account for one-third of the world’s primary crop production, therefore legume production is relevant to meet the necessity for feed and food. The key to the success of this plant family was the evolution of a mutualistic symbiosis with N-fixing bacteria of the family Rhizobiaceae to fix atmospheric N for plant growth. The effective interaction between rhizobia and legumes results in a novel plant organ, the root nodule. The differentiated bacteroids, established in the nodules, reduce atmospheric N to ammonia through the action of the nitrogenase enzymatic complex. In turn, ammonia is assimilated into organic N compounds in the nodule. Legumes play an important role in sustainable agriculture (Graham & Vance, 2003).
Rhizobial root infection and the formation of root nodule primordia are induced by compounds known as Nod factors which are secreted by the bacteria. Genetic and genomic studies have revealed several legume genes that are essential for Nod factor perception, rhizobial infection and subsequent steps of signal transduction cascades that result in nodule formation, including receptor, receptor kinase, kinase and transcription factor (TF) genes (reviewed by Oldroyd & Downie, 2004). However, to date the regulatory functions of miRNAs in the legume–rhizobia symbiosis have been largely unexplored (reviewed by Simon et al., 2009). Only two miRNAs have been reported to be relevant to nodule development in the model legume Medicago truncatula. Combier et al. (2006) demonstrated that Mtr-miR169 post-transcriptionally regulates the CCAAT-binding complex HAP2-type TF (HAP2.1) TF which is a key regulator of nodule development. In contrast, Boualem et al. (2008) reported that Mtr-miR166 down-regulates the expression of the class -III homeodomain-leucine zipper (HD-ZIP III) TF in symbiotic nodule and lateral root development.
In silico studies have detected conserved miRNAs in several species of the Fabaceae family (Zhang et al., 2006; Sunkar & Jagadeeswaran, 2008). Recent high-throughput sequencing technologies have allowed the identification of novel miRNAs in soybean (Glycine max) and M. truncatula. In soybean, Subramanian et al. (2008) identified 35 novel miRNA families; a subset of these responded to root inoculation with Bradyrhizobium japonicum and were expressed during early inoculation stages. In addition, Wang et al. (2009) identified 22 miRNAs specific to soybean and four novel miRNAs from mature nodules. Recently, Joshi et al. (2010) utilized deep sequencing and bioinformatic approaches to identify 87 novel miRNAs. Target genes for recently identified soybean miRNAs have been predicted (Zhang et al., 2008; Wang et al., 2009; Joshi et al., 2010). Regarding M. truncatula, Jagadeeswaran et al. (2009) reported eight novel miRNAs from shoot:root libraries, four of which were annotated as specific. Zhou et al. (2008) identified a total of 26 new miRNA candidates using a computational approach and confirmed their expression in various M. truncatula organs and in the leaves in response to heavy metals. Szittya et al. (2008) identified novel miRNA candidates from the leaves of this legume. Recently, a genome-wide analysis of miRNAs based on deep sequencing of RNAs from nodules and root apexes identified 100 novel candidate miRNAs encoded by 265 hairpin precursors which were mapped in the M. truncatula genome (Lelandais-Briere et al., 2009).
Common bean (Phaseolus vulgaris) is the most important grain legume for direct human consumption. Environ-mental factors such as low soil N and P concentrations and acid soil conditions are important constraints for common bean production in most areas of Latin America and Africa where the crop is grown (Broughton et al., 2003; Graham et al., 2003). We are interested in examining the adaptations that common bean has evolved to cope with nutrient deficiency stresses (Hernández et al., 2007, 2009). We are also interested in deciphering the complex regulatory mechanisms that may involve miRNAs along with other key regulators. Valdés-López et al. (2008) demonstrated that the MYB-DNA binding domain (MYB) TF P. vulgaris phosphate starvation response 1 (PvPHR1) and the miRNA PvmiR399 play essential roles in P-deficiency signaling in common bean roots. Recently, Arenas-Huertero et al. (2009) identified several conserved and six novel miRNAs found in small RNA libraries obtained from common bean seedlings under various treatments such as drought stress, ABA addition and Rhizobium tropici inoculation. Common bean target mRNAs were predicted or demonstrated for some of the miRNAs identified and expression was verified in seedlings, but not in nodules (Arenas-Huertero et al., 2009). However, information about the role of miRNAs in regulating the responses to nutritional stresses in common bean is scarce.
The aim of this work was to determine the expression profile of selected miRNAs, including conserved and nonconserved miRNAs, from soybean and common bean. The expression of miRNAs was analyzed in leaves, roots and nodules of common bean plants grown in full-nutrient (control) and nutrient stress conditions using miRNA macroarray and miRNA blot analyses. Our data extend knowledge of miRNAs with putative relevant roles in the development, function or stress response of legume nodules, essential organs for symbiotic N fixation.
Materials and Methods
Plant material and growth conditions
The common bean (Phaseolus vulgaris L.) Mesoamerican cv Negro Jamapa 81 was used in this study. Seeds were surface-sterilized and germinated on sterile and moist vermiculite at 25°C for 3 d. Seedlings were transplanted to plastic boxes containing 8 l of Franco/Munns nutrient solution (Franco & Munns, 1982). The nutrient solution was aerated with aquarium air pumps; the volume and pH (6.5) were adjusted daily. Plants were grown in the described hydroponic system in a glasshouse under controlled environment conditions (25–27°C, 70% humidity, and natural illumination). For symbiotic conditions, N-free Franco/Munns nutrient solution was used. Three days after planting, each plastic box was inoculated with 5 ml of a saturated (overnight) liquid culture of Rhizobium tropici CIAT 899. In experiments with plants grown in full-nutrient conditions (control), leaves and roots were collected from nonsymbiotic plants 14 d after planting and mature nodules were collected from inoculated plants 19 d post-inoculation (dpi).
For nutrient stress growth conditions, the plant solution was changed 7 d after planting for nonsymbiotic plants or 12 d after planting when inoculated plants had already formed nodules. To induce P or iron (Fe) deficiency (hereafter abbreviated as Pd and Fed, respectively), the P or Fe concentration of the nutrient solution was reduced to 2 μM, which represents, respectively, a 100- or 50-fold lower concentration compared with the full-nutrient medium. For N deficiency (abbreviated as Nd), the solution was depleted of any N source. To induce manganese (Mn) toxicity (abbreviated as Mnt), the nutrient solution was supplemented with 200 μM MnCl2. For acidic conditions (abbreviated as Ac), the pH of the nutrient solution was adjusted and maintained at 5.5. Nonsymbiotic plants or plants inoculated with R. tropici were grown in nutrient stress conditions for 7 d before tissues were harvested for analyses.
Both control and stress treatments consisted of three independent plastic boxes, with eight seedlings per box (24 plants in total). Harvested tissues (leaves, roots, or nodules) were immediately frozen in liquid N2 and stored at −80°C until used for RNA isolation.
Total RNA was isolated from 1 g of frozen leaves, roots, or nodules from control or stress-treated (Pd, Fed, Nd, Ac, or Mnt) common bean plants as reported previously (Valdés-López et al. (2008). For enrichment of miRNAs, 100 μg of total RNA samples were fractionated and cleaned using the flashPAGE fractionator and flashPAGE Reaction Clean-up, respectively, following the manufacturer’s recommendations (Ambion). These samples (hereafter termed ‘miRNA samples’) were stored at −80°C until tested.
Preparation and hybridization of miRNA macroarrays
Sixty-eight synthetic DNA oligonucleotides (18–24 nts) corresponding to reverse complementary sequences of selected mature miRNAs were synthesized. Twenty-four of these DNA oligonucleotides correspond to miRNA families that are conserved in different plant species (Zhang et al., 2006; Sunkar & Jagadeeswaran, 2008). Thirty-five DNA oligonucleotides correspond to miRNAs cloned from soybean (Glycine max) roots inoculated with Bradyrhizobium japonicum (Subramanian et al., 2008). Another nine DNA oligonucleotides correspond to miRNAs cloned from common bean seedlings (Arenas-Huertero et al., 2009). Additionally, two oligonucleotides corresponding to T7 and M13 bacteriophage promoters were used as negative controls as these did not show complementarity to any known miRNAs. Sequences of each oligonucleotide probe are provided in Supporting Information Table S1. Each probe was manually spotted on 2 × 3 cm Amersham Hybond-N+ membranes (GE Healthcare, Piscataway, NJ, USA), dried at room temperature, and UV cross-linked three times. Printed membranes (hereafter termed ‘miRNA macroarrays’) were wrapped in aluminum foil and stored at −20°C until used for hybridization.
MiRNA samples isolated from the leaves, roots, or nodules of control or stress-treated common bean plants were used for miRNA macroarray hybridization. MiRNA samples were dephosphorylated with Antarctic Phosphatase (New England Biolabs, Beverly, MA, USA) and then radioactively labeled with T4 polynucleotide kinase (PNK) (New England Biolabs) and [γ-32P]-ATP (Perkin-Elmer, Santa Clara, CA, USA). The labeling reaction was performed at 37°C for 1 h and stopped by incubation at 90°C for 5 min; the probe was then incubated in ice for 3 min. The miRNA macroarrays were pre-hybridized in 1 ml of ULTRAhyb-Oligo Hybridization Buffer (Ambion) at 37°C for 1 h. The labeled miRNA samples were hybridized in hybridization solution for 15 h at 37°C. After hybridization, the miRNA macroarrays were washed twice in 2X SSC/0.1X SDS for 15 min at 37°C and then washed a further three to five times with the same washing solution and at the same temperature for 6 min each time. The membranes were then exposed to a Phosphor Screen System (GE Healthcare) for 1 d. The phosphor screen was scanned in a Storm 860 Gel and Blot Imaging System (GE Healthcare). Three independent miRNA macroarrays were hybridized with miRNAs isolated from three different biological replicates of each treatment and organ.
Data analysis of miRNA macroarrays
The signal intensity of each spot of the miRNA macroarrays was quantified using ImageQuant 5.2 software (Molecular Dynamics, Sunnyvale, CA, USA). In order to include only highly reproducible experiments in the analysis, linear regression analysis was performed for each pair of membrane replicas for each treatment; only those replicates for which the linear model could explain at least 80% of the variation (r2 ≥ 0.8) were considered. The miRNA signal intensity data are provided in Table S2. The signal intensity data were normalized with the average of the signal intensity of the printed pvu-miR482* which has shown no significant variation across all the conditions tested (Arenas-Huertero et al., 2009, and this work). The normalized data were then used to analyze the level of expression of each miRNA in the different organs – leaves, roots, or nodules – from plants grown in control conditions.
For analysis of the differential expression of miRNAs in leaves, roots or nodules from nutrient-stressed plants, the average normalized expression ratios (stressed:control) were obtained and subjected to Student’s t-test. The expression data for differentially regulated miRNAs selected (P ≤0.05) were then used for principal component analysis (PCA) (Pearson, 1901) and hierarchical cluster analysis (HCA) (Eisen et al., 1998). An expression profile matrix was built representing the expression ratio values (stressed:control) for each treatment in each organ for each miRNA selected. The expression profile matrix was imported into the MultiExperiment Viewer program (MeV; http://www.tm4.org/). PCA was performed using MeV with the ‘cluster sample’ option and without any centering mode selected. HCA was performed using MeV with the following options selected: ‘gene tree’, ‘optimize gene leaf order’, ‘Manhattan distance’, and ‘complete linkage clustering’.
miRNA blot analysis
Total RNA (20 μg), isolated as reported previously (Valdés-López et al., 2008), was separated using 15% PAGE/8 M urea/1x TBE buffer. The gel was electro-blotted to Hybond-N+ membrane (GE Healthcare) and then UV cross-linked twice. Synthetic DNA oligonucleotides with the antisense sequence corresponding to miRNAs (Table S1) were used as probes after 5′-end-labeling using [γ-32P]-ATP (Perkin-Elmer) and T4 PNK (New England Biolabs). As a loading control, a DNA oligonucleotide complementary to U6 snRNA was used as a probe. The probes were purified with Quick spin oligo columns (Roche) before addition to the hybridization solution. Hybridizations were performed at 42°C for 15 h in UltraHyb-oligo solution (Ambion). Hybridized membranes were washed twice in 2x SSC/0.1% SDS for 30 min each time, and then exposed to the Phosphor Screen System (GE Healthcare). Each miRNA blot was repeated three times. The signal intensity of each hybridization band was quantified as described in the Data analysis of DNA macroarray section. Average normalized signal intensity values were used to obtain the expression ratios (stressed:control) of nutritional responsive miRNAs.
Target sequence prediction
To determine the potential targets of miRNAs expressed in common bean, we used M. truncatula (version 9.0), soybean (version 14.0), and bean (version 3.0) Dana Farber Cancer Institute (DFCI) Gene Indices (http://compbio.dfci.harvard.edu/tgi/). As a general approach, we used the psRNATarget Server (http://bioinfo3.noble.org/psRNATarget/) which can identify putative targets that may be regulated at post-transcriptional or at translational levels. Mature miRNA sequences were used as queries to search for potential target mRNAs in the soybean and M. truncatula databases. Results from these analyses were individually inspected to consider candidates according to parameters recently established for plant miRNAs (Allen et al., 2005; Voinnet, 2009). Once the putative target mRNA was identified in the soybean and M. truncatula databases, we searched the DFCI Bean Gene Index for the ortholog of each target mRNA, in order to predict targets for common bean (Table S3).
Real-time quantitative RT-PCR (qRT-PCR) analysis
Transcript levels of selected common bean miRNA target genes were quantified by the one-step assay using the iScript One-Step RT-PCR Kit with SYBR Green (Bio-Rad) in a 96-well format with the iQ5 Real-Time PCR Detection System and iQ5 Optical System Software (Bio-Rad), as previously reported (Hernández et al., 2009), with the following minor modifications. Each qRT-PCR reaction contained 50 ng of RNA template, previously treated with DNase (Qiagen). The PCR cycling temperature was set to 55°C in the thermal cycler. For each reaction, a product of between 100 and 200 bp could be visualized on an agarose gel. Each assay included at least two no template controls (NTCs) in which RNA was substituted by DNase-RNase free water; no amplification was obtained for NTCs. Dissociation curves for each amplicon were carefully examined to confirm the specificity of the primer pairs used (Table S4). Relative transcript levels for each sample were obtained using the ‘comparative Ct method’. The threshold cycle (Ct) value obtained after each reaction was normalized to the Ct value of the elongation factor 1 (EF1) gene whose expression was consistent across the conditions. The relative expression level was obtained by calibrating the ΔΔCt values for the stressed conditions used and the normalized Ct value (ΔCt) for the controls for the same nutrient and organ.
Inductively coupled plasma mass spectroscopy (ICP-MS) analysis and nitrogenase activity
The ICP-MS analysis for shoots and roots from nonnodulated plants was performed as reported by Jain et al. (2009). Nitrogenase activity from the bacteroids established in the nodules was determined from detached, 21-dpi nodulated roots using the acetylene reduction assay as reported by Mendoza et al. (1995).
In this work we analyzed the miRNA expression profile in leaves, roots and nodules of common bean plants grown in full-nutrient (control) conditions or under nutrient deficiencies (Pd, Nd, or Fed), Ac or Mnt for 7 d. The hydroponic growth conditions used are described in the Materials and Methods section.
The nutritional status of plants from each treatment was determined by ICP-MS (Fig. 1). Compared with control plants, a reduction of 2- to 3-fold in N, P, and Fe content was observed in Nd, Pd, and Fed plants, respectively (Fig. 1a–c), whereas a marked increase in Mn content was found in Mnt plants (Fig. 1d). A deficiency or excess of one nutrient may cause secondary alterations in the uptake and internal concentration of other nutrients. This is thought to be related to an altered metal homeostasis response which involves common ligands and transporters of metal ions (reviewed by Grotz & Guerinot, 2006; Haydon & Cobbett, 2007). Our data support those interactions of nutrients. For example, Nd and Fed plants showed c. 2-fold increases in Mn and Cu contents (Fig. 1d,f), while Pd and Mnt plants showed significantly reduced calcium (Ca) content (Fig. 1e). For Ac plants, a c. 2-fold decrease in Mn, Ca, and Cu was observed (Fig. 1d–f). Plants grown in each stress treatment showed characteristic visible stress symptoms. Nd plants had chlorotic and purple leaves; Fed plants had chlorotic leaves, and Mnt plants had leaves with brown lesions (Fig. S1). In addition, Pd, Nd, and Ac plants showed a decrease in dry weight, whereas the dry weights of Fed and Mnt plants were not affected (Fig. 2a).
N-fixing common bean plants inoculated with R. tropici were subjected to similar stress treatments, except for Nd. While the dry weight of stressed nodulated plants was not significantly different from that of control nodulated plants (data not shown), symbiotic N fixation was affected by the stress treatments (Fig. 2). The nodule dry weight of Pd, Ac, and Mnt plants was c. 2-fold lower than that of control plants (Fig. 2b). The total nodule nitrogenase activity of the bacteroids was 1.5- to 3-fold lower in stressed plants compared with control plants (Fig. 2c).
miRNA expression profile in common bean plants
Arenas-Huertero et al. (2009) reported the expression of 19 conserved and six novel miRNAs in common bean tissues or in seedlings subjected to drought, abscisic acid, cold or high salt. However, their study did not include miRNA expression in nodules. In this work we analyzed the expression of 68 miRNAs under various abiotic stress conditions in leaves and roots as well as nodules using miRNA macroarray analysis. The miRNA macroarray used in our studies contained probes for nine miRNAs from common bean (Arenas-Huertero et al., 2009), 24 conserved miRNAs that have been detected in various legumes (Zhang et al., 2006; Sunkar & Jagadeeswaran, 2008) and 35 miRNAs from soybean as reported by Subramanian et al. (2008) (Table S1). Soybean and common bean are members of the Phaseoloid/Millettioid clade of legumes and are phylogenetically related (Doyle & Luckow, 2003).
The first step in this study was to determine the expression profile of miRNAs in leaves, roots, and nodules of common bean plants grown under full-nutrient (control) conditions. Table 1 shows the normalized expression levels of various miRNAs from the miRNA macroarray. Thirty-three miRNAs (21 conserved; seven from common bean, including pvu-miR482*, which was used for normalization; and five from soybean) were detected as being expressed at different levels in these organs. Nineteen miRNAs (11 conserved, five from common bean, and three from soybean) were commonly expressed in the three organs. All except one of the miRNAs were detected in the leaves. A total of 22 miRNAs were detected in common bean nodules, two of which were also present in leaves. miR172 was only detected in the nodules.
Table 1. MicroRNA (miRNA) expression in leaves, roots and nodules of common bean plants grown under sufficient nutrient conditions
aAverage of normalized signal intensity values from three biological replicates of miRNA macroarrays.
nd, not detected.
The differential regulation of miRNAs under biotic and abiotic stress conditions, including P, Cu, and S deficiency, has been reported in Arabidopsis (Bari et al., 2006; Yamasaki et al., 2008; Kawashima et al., 2009). However, there have been no reports on miRNA expression under nutritional and/or heavy metal toxicity stresses in common bean. In this work we used miRNA macroarray hybridization to identify miRNAs differentially regulated in common bean organs from plants subjected to abiotic stress, including Pd, Nd, Fed, Ac and Mnt treatments. Expected stress phenotypic symptoms were observed in each treatment (Figs 1 and 2). We identified a total of 37 miRNAs that were differentially regulated under stress conditions. These included miRNAs expressed in control plants (Table 1) and another five miRNAs (pvu-miR1514a, gma-miR1511, gma-miR1513, gma-miR1515 and gma-miR1516) that were only detected under stress conditions.
We performed PCA to explore the overall structure of the miRNA macroarray data in terms of the variance component. PCA is a method that involves transformation of possibly correlated variables into a smaller number of uncorrelated variables called principal components (PCs) (Pearson, 1901). PCA is an excellent exploratory data analysis tool for revealing the internal structure of the data in a way that best explains the variance in the data. The PCA revealed three major PCs that explained 31.4, 21.6, and 14% of the total variability in the data, respectively. On a PCA plot with PC1 and PC2, we observed clustering of stress treatments in the three organs into three different groups (Fig. 3). Each group may represent a similar miRNA expression pattern for different stress treatments and organs. The Mnt and Pd treatments in nodules were separated from the others along the first PC axis, suggesting a distinct miRNA expression pattern under Mnt and Pd conditions compared with other treatments in nodules (Fig. 3). All five treatments in leaves were closely clustered together, suggesting that the miRNAs selected responded similarly under these stress conditions in leaves. Interestingly, the root Nd and Pd treatments were clustered more closely with leaf treatments but separated from the remainder of the root treatments (Fig. 3). This suggests that the miRNA expression pattern under Nd and Pd stress conditions is distinct from that under other treatments in roots but may be more similar to the stress responses in leaves. Clustering of treatments into groups in a PCA plot suggests that multiple stress signals might cross-talk to each other and may be integrated to change the global miRNA expression pattern in each organ. A different pattern of clustering for different organs also suggests that signal integration may occur differently in different organs and miRNAs may respond differently for the same stress signal or combination of multiple signals in different organs.
We performed HCA to examine clustering pattern for stress-responsive miRNAs (Fig. 4). The miRNAs differentially regulated under various stress conditions in the three organs could be classified into five major groups based on their expression pattern (Fig. 4). Group I includes miRNAs that were strongly responsive to the stress treatments in nodules (mostly up-regulated). This group includes miR319 and miR398, which responded to all the stress treatments in one or more organs; this may reflect a general response to oxidative stress, which is produced by all the stress treatments. It has been proposed that miR398 targets a superoxide dismutase in common bean and in other plants (Arenas-Huertero et al., 2009; Table S3); such enzymes play important roles in the oxidative stress response. These two miRNAs were up-regulated under Mnt and Pd stress conditions but down-regulated by Fed and Ac stress treatments in nodules, which is in agreement with the separation of this pair of treatments in the PCA (Figs 3 and 4). Nodules from common bean plants subjected to Pd stress showed accumulation of organic and polyhydroxy acids and up-regulation of genes coding for enzymes of the carbon fixation and glycolysis metabolic pathways (Hernández et al., 2009). Mnt bean plants also showed up-regulation of genes for carbon metabolic pathways (O. Valdés-López & G. Hernández, unpublished results) and exudation of organic acids has been reported for Mnt roots (Horst et al., 1999; Mora et al., 2009). These data indicate that miRNAs that respond both in Pd and in Mnt nodules, and are clustered in the PCA (Fig. 3), may be involved in the regulation of increased nodule carbon metabolism under these two stresses. Groups II and III include miRNAs that were strongly responsive to the stress treatments in roots and leaves (mostly down-regulated), respectively. Group IV includes miRNAs that were weakly responsive to the stress treatments (mostly up-regulated) in roots and nodules. Most of the miRNAs in this group showed no response under Nd and Pd conditions in roots but were differentially regulated (mostly up-regulated) by Fed, Ac, and Mnt stress treatments in roots. The latter agrees with the PCA where Fed, Ac, and Mnt in roots were clustered (Fig. 3) and may be related to the close inverse relationship of Mn and Fe concentrations at the cellular level in several plant species; toxic Mn concentrations in acidic soils have been associated with plant responses to Fed (Korshunova et al., 1999; Izaguirre-Mayoral & Sinclair, 2005). Most of the miRNAs in group IV did not respond to all five stresses in leaves (Fig. 4). Group V includes miRNAs that were responsive to nearly all the stresses (mostly up-regulated) in the three organs analyzed.
Northern blot expression analysis of selected miRNAs
We selected three stress-responsive miRNAs from each organ, including both up-regulated and down-regulated examples, to validate the expression ratios obtained in the miRNA macroarray experiments using the alternative method of northern blot analysis (Fig. 5). The pattern of expression obtained using the macroarrays was confirmed for each miRNA, with the exception of miR157 in leaves (Fig. 5). This corresponds to c. 80% validation of macroarray results with respect to expression patterns. However, there was variation in the expression ratio for each tested miRNA when the values obtained from macroarrays were compared with those from northern blot analysis. This could be attributable to different sensitivities of the two technologies.
Targets for miRNAs present in common bean
We identified the putative target genes for the 38 miRNAs expressed in common bean (Table 1, Fig. 4). Several targets already reported either in Arabidopsis or other legumes, such as M. truncatula and soybean, could also be proposed for common bean (Arenas-Huertero et al., 2009; Table S3). Whenever an Arabidopsis target gene had not been reported for legumes, we searched for orthologs in M. truncatula, soybean and common bean gene sequence data bases. Sixteen out of 21 conserved miRNAs expressed in common bean were predicted to target genes that are orthologs of those reported for Arabidopsis, M. truncatula and/or soybean (Arenas-Huertero et al., 2009; Table S3). Most of these target genes were annotated as TFs from different gene families and other regulatory proteins such as an ubiquitin conjugase and a receptor. However, no common bean target orthologous gene could be assigned for miR159, miR165, miR166, miR168, and miR390 (Table S3).
For the identification of other (novel) putative targets for miRNAs expressed in P. vulgaris, we performed in silico analyses using the psRNAtarget Server to screen expressed sequence tag (EST) entries from the DFCI Bean Gene Index (v. 3.0). The EST matches resulting from such analyses were individually inspected to identify potential targets using parameters previously defined to identify plant miRNA targets (Allen et al., 2005; Voinnet, 2009). Table 2 shows 13 candidate common bean target genes for 11 miRNAs; three conserved, three common bean and five soybean miRNAs. The majority of target genes for the miRNAs analyzed in this work (Table 2, Table S3) can be assigned to TF genes, suggesting a crucial role for miRNAs in combination with TF target genes in plant signaling pathways (Hobert, 2008). However, other proposed targets for common bean miRNAs code for proteins that may also play crucial roles in regulation or signal transduction, such as F-box proteins or calcium-dependent protein kinases (Table 2, Table S3).
Table 2. Predicted Phaseolus vulgaris mRNA targets for microRNAs (miRNAs)
aTentative consensus (TC) sequences assigned using the Dana Farber Cancer Institute (DFCI) Bean Gene Index, version 3.0, or GenBank accession number for singletons.
bAnnotation updated by comparing expressed sequence tag (EST) sequences with proteins from the UniprotKB database, release 15.8.
cWatson–Crick base pairing is indicated by a ‘|’; G:U base pairing by a ‘:’; and ‘-’ indicates a mismatch.
(B3IX28) Transcription factor CAAT
(C6ZRT7) Serine/threonine protein kinase
(Q9ZRV5) Basic blue copper protein
(B9H216) F-box family protein
(B9RSD4) GTP-binding protein
(B9T2U0) Calcium-dependent protein kinase
(Q93VN8) NBS-LRR resistance-like protein B11
(P46254) Heat shock protein 22KDa protein, mitochondrial
(Q39822) Pip1 protein
(B3IX30) Transcription factor AP2-EREBP
(B9S708) Receptor protein kinase CLAVATA1
(B9S3W2) Transport inhibitor response 1 protein
In order to investigate the possible effect of miRNAs on their potential targets, we examined the expression pattern of common bean target genes in different organs of stressed plants. We selected seven target genes (Table 3) whose cleavage by the conserved common bean miRNAs was validated by rapid amplification of 5′ complementary DNA ends (5′ RACE) in a previous study (Arenas-Huertero et al., 2009). Selected target gene transcript levels for control and stressed plant organs were determined by qRT-PCR. Table 3 shows the target gene expression ratios (stressed:control) for differentially expressed miRNAs selected in this study. A negative correlation between the expression of an miRNA and that of its respective target gene has been observed in many cases (Abdel-Ghany & Pilon, 2008). Most of the target genes we analyzed showed an inverse correlation with the corresponding miRNA expression; that is, the target gene of an up-regulated miRNA showed down-regulated expression (Table 3). In addition, as reported for other plants (Jeong et al., 2009), a similar expression pattern between a target gene and its corresponding miRNAs was observed in some cases (Table 3).
Table 3. Expression ratios of selected microRNAs (miRNAs) and their target mRNAs
Expression ratio (stressed : control)
Target and miRNA expression levels showing a negative correlation are highlighted in bold. Treatments: Pd, phosphorus deficiency; Nd, nitrogen deficiency; Fed, iron deficiency; Ac, acidic pH (5.5); Mnt, manganese toxicity.
aTranscript levels were determined by quantitative reverse transcriptase–polymerase chain reaction (qRT-PCR) . Values represent the normalized expression ratios, given as the average of three biological replicates.
bValues from miRNA macroarray analysis (Fig. 4). For those miRNAs that were detected in the controls but for which the signal fell below the level of detection under stress conditions, the expression ratio was given a value of ‘0’.
We previously reported that the expression of UBC24 or PHO2, the target of miR399, is down-regulated in the leaves and roots of Pd common bean plants (Valdés-López et al., 2008), where miRNA399 was found to be up-regulated. This is in agreement with results from Arabidopsis (Bari et al., 2006; Chiou et al., 2006). In this study, miR399 was up-regulated under Pd but down-regulated under Nd conditions both in leaves and in roots (Fig. 4). The putative miR399 target gene (PHO2/UBC24) in M. truncatula showed the opposite expression pattern (down- and up-regulation) under Pd and Nd conditions, respectively (S. Yang, unpublished results).
Despite the great diversity and agronomic importance of the Fabaceae (legume) family (Doyle & Luckow, 2003), knowledge of the regulatory roles of miRNAs in legumes is scant (Simon et al., 2009). In common bean, only nine novel miRNAs have been identified (Arenas-Huertero et al., 2009) but their expression pattern and roles have not been thoroughly analyzed.
In this work, a total of 38 miRNAs were detected in common bean control and stressed plants in macroarray hybridization analysis. Another 30 miRNAs, mainly from soybean, were not detected under any conditions tested. With the exception of gma-miR1507 and gma-miR1509 (Subramanian et al., 2008; Wang et al., 2009), no information about the expression profile of undetected soybean miRNAs could be found. In light of the species, organ or physiological condition specificity of the miRNAs, it is possible that orthologs of some soybean miRNAs are absent in common bean. In addition, it is possible that the miRNA macroarray approach used in our work may not be sensitive enough to detect miRNAs that are expressed at very low levels in soybean and/or common bean.
The majority of the miRNAs detected in common bean plants were found in more than one plant organ (leaves, roots, and nodules). These findings may be interpreted as reflecting the expression of a given miRNA precursor gene in various plant organs and/or the systemic transmission of npcRNAs as long-distance signals in plants (Jorgensen, 2002; Yoo et al., 2004; Lough & Lucas, 2006). Although the identification of miRNAs in common bean phloem has not been reported, known miRNAs have been identified in cucurbits and in oilseed rape (Brassica napus) phloem (Yoo et al., 2004; Buhtz et al., 2008; Pant et al., 2008, 2009). The latter include miR399, miR398, and miR395, which participate in P, Cu and S homeostasis, respectively. The level of each miRNA has been found to increase in the pholem sap of oil rape seed plant under the corresponding P. Cu or S starvation (Buhtz et al., 2008). We detected miR399 both in common bean leaves (control, and Pd-, Ac- and Mnt-stressed) and in Pd roots, where it plays an essential role in P homeostasis (Valdés-López et al., 2008). These findings are in agreement with the shoot–root transport of miR399, as reported for Arabidopsis (Buhtz et al., 2008).
miR172 was the only miRNA detected exclusively in common bean nodules and not in other tested organs. It was slightly increased in nodules from Pd, Fed and Mnt plants. Consistent with this, miR172 was most abundant in N-fixing nodules of soybean and M. truncatula (Lelandais-Briere et al., 2009; Wang et al., 2009). In Arabidopsis, miR172 and its target APETALA2-related (AP2) TF play a major role in regulating stem cell fate in the floral meristem, organ identity, flowering time and photoperiod (Aukerman & Sakai, 2003; Chen, 2004; Jung et al., 2007; Zhao et al., 2007). Orthologous AP2 target genes have been proposed for soybean, M. truncatula, and common bean (Zhang et al., 2008; Arenas-Huertero et al., 2009; Lelandais-Briere et al., 2009). Common bean AP2 TFs respond to P starvation in roots and nodules (Hernández et al., 2007, 2009). Here we detected down-regulated expression of the AP2 target gene in Mnt nodules, where miR172 was up-regulated. Taken together, these data suggest a crucial role of miR172 in the process of nodule development and/or in nodule response to stresses in different legume species, including common bean (Simon et al., 2009).
The 37 miRNAs identified as stress-responsive in common bean plants include numerous miRNAs previously reported to be plant stress responsive. For example, miR398 and miR408 were found to be responsive to Cu deficiency in Arabidopsis (Abdel-Ghany & Pilon, 2008; Yamasaki et al., 2008). Arenas-Huertero et al. (2009) reported that pvu-miR2118 and pvu-miR159.2 were responsive to drought and salinity in common bean. miR399 was responsive to P deficiency in Arabidopsis and common bean (Bari et al., 2006; Chiou et al., 2006; Valdés-López et al., 2008). However, we identified numerous novel stress-responsive miRNAs. For example, in Mnt common bean plants 11 miRNAs (miR157, miR156, miR170, miR172, miR319, miR398, pvu-miR159.2, pvu-miR2118, gma-miR1508, gma-miR1526, and gma-miR1532) were strongly induced in nodules and another 11 miRNAs (miR160, miR397, miR399, miR408, pvu-miR1509, pvu-miR1514a, gma-miR1510, gma-miR1511, gma-miR1513, gma-miR1515, and gma-miR1516) were strongly inhibited in leaves or roots. Of these, miR160, miR166, miR319, miR393, and miR398 responded to mercury, cadmium and aluminum stresses in M. truncatula (Zhou et al., 2008); however, there is no information in the literature about the expression or roles of miRNAs under Mnt stress for any plant species. In addition, we detected for the first time a total of 10 miRNAs (miR157, miR160, miR165/miR166, miR169, miR393, pvu-miR2118, gma-miR1524, gma-miR1526, and gma-miR1532) differentially regulated under Pd in one or more common bean organs that have never been reported as P stress-responsive in other plant species.
In agreement with previous studies (Grotz & Guerinot, 2006; Haydon & Cobbett, 2007), we found that changes in the availability of one nutrient could affect the availability of other nutrients, resulting in unexpected interactions between miRNAs. For example, we found that Cu content was increased in common bean plants under Nd and Fed, where miR398 and miR408 were down-regulated, while Cu was decreased in Ac and Mnt, where miR398 was up-regulated. These data are in agreement with results reported for Arabidopsis by Yamasaki et al. (2009), who found that SQUAMOSA promoter binding protein-like 7 (SPL7) activated the transcription of miR397, miR398, and miR408 under low-Cu conditions.
Our HCA for stress-responsive common bean miRNAs revealed that some miRNAs showed similar expression patterns under the same stress conditions in different organs. This suggests their possible interaction in response to the same nutrient stress. For example, pvu-miR1511, gma-miR1513, gma-miR1515, and gma-miRNA1516 were strongly increased, specifically, in Fed leaves, and it is therefore possible that they participate in the Fed signal transduction pathway in this organ.
Several previous studies that utilized systematic approaches to examine the effect of multiple signals (i.e. carbon, nitrogen, and light deficiency) on global gene expression in plants suggested significant effects of signal cross-talk and signal integration on global gene expression in Arabidopsis (Gutiérrez et al., 2007; Krouk et al., 2009). Krouk et al. (2009) also suggested that signal integration occurs differently in different organs, resulting in different gene expression patterns in organs subjected to the same conditions. Our miRNA PCA and HCA data also suggest that miRNAs may be involved in stress signal transduction pathways that cross-talk with each other, resulting in coordinated downstream miRNA expression patterns in different common bean organs. For example, miR157, miR156, miR167, miR319, and miR398 responded to all the stresses/signals in all the plant organs tested, while pvu-miR2118 and pvu-miR2119 were up-regulated in bean nodules under the four stress treatments tested.
Some target genes analyzed in this work showed an inverse correlation with their corresponding miRNA expression. However, we also found that the expression level of certain target mRNAs was not decreased by the induction of the corresponding miRNAs, even if cleavage of the corresponding target was detected. Similar results have been observed for miRNAs from other plants (Jeong et al., 2009), implying that the post-transcriptional regulation of target mRNA levels by miRNA-directed cleavage is not always rate-limiting for mRNA accumulation under specific conditions. Alternatively, other members of a multigene family may be targeted by the same miRNA in different tissues; if this is the case, then the potential target transcripts for the miRNAs found in this work remain to be identified. Translational repression could also be an alternative mode of regulation for some common bean miRNA target genes. For example, previous studies suggested translational repression of AP2-like genes by miRNA172 as a predominant mode of action, even though post-transcriptional regulation (cleavage) could still be observed (Aukerman & Sakai, 2003; Chen, 2004; Chuck et al., 2008b; Zhu et al., 2009).
Two miRNAs, pvu-miR2118 and gma-miR1510, have been proposed to target nucleotide-binding site–leucine rich repeat (NBS-LRR) resistance-like proteins in common bean and M. truncatula (this work; Jagadeeswaran et al., 2009; Arenas-Huertero et al., 2009). These proteins confer resistance to a wide variety of plant pathogens, but their expression is also induced in legume nodules of M. truncatula, L. japonicus and common bean (Colebatch et al., 2004; Tesfaye et al., 2006; Peltzer-Meschini et al., 2008). It has been postulated that the NBS-LRR resistance gene family may play a relevant role in symbiotic plant–microbe interactions, perhaps by suppressing defense responses upon recognition of symbiotic partners.
This work contributes to the discovery of novel nutrient stress-responsive miRNAs in common bean and provides a foundation for the evaluation of the individual roles of miRNAs in post-transciriptional regulation of developmental processes and stress responses in this agronomically important legume. Current work by our group is aimed at functional characterization of selected miRNAs in common bean using genetic approaches, as previously reported (Valdés-López et al., 2008).
This work was supported in part by Consejo Nacional de Ciencia y Tecnología, Mexico (CONACyT) (grant 083206) and by the US Department of Agriculture (grant USDA-FAS MX161). O.V.L. was a PhD student from Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México and a recipient of a studentship from CONACyT (200048). We are grateful to Sue Miller, Bruna Bucciarelli, and Jeffrey Roessler for technical support and for hosting O.V.L. at the University of Minnesota/USDA and to Victor M. Bustos at CCG-UNAM for plant maintenance.