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ENVIRONMENTAL STRESS AND ADAPTATION TO STRESS

Identification of Nutrient-Responsive Arabidopsis and Rapeseed MicroRNAs by Comprehensive Real-Time Polymerase Chain Reaction Profiling and Small RNA Sequencing^{1,[C],[W],[OA]}

Max-Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany

	ABSTRACT

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 
Comprehensive expression profiles of Arabidopsis (Arabidopsis thaliana) MIRNA genes and mature microRNAs (miRs) are currently not available. We established a quantitative real-time polymerase chain reaction platform that allows rapid and sensitive quantification of 177 Arabidopsis primary miR transcripts (pri-miRs). The platform was used to detect phosphorus (P) or nitrogen (N) status-responsive pri-miR species. Several pri-miR169 species as well as pri-miR398a were found to be repressed during N limitation, whereas during P limitation, pri-miR778, pri-miR827, and pri-miR399 species were induced and pri-miR398a was repressed. The corresponding responses of the biologically active, mature miRs were confirmed using specific stem-loop reverse transcription primer quantitative polymerase chain reaction assays and small RNA sequencing. Interestingly, the latter approach also revealed high abundance of some miR star strands. Bioinformatic analysis of small RNA sequences with a modified miRDeep algorithm led to the identification of the novel P limitation-induced miR2111, which is encoded by two loci in the Arabidopsis genome. Furthermore, miR2111, miR169, a miR827-like sequence, and the abundances of several miR star strands were found to be strongly dependent on P or N status in rapeseed (Brassica napus) phloem sap, flagging them as candidate systemic signals. Taken together, these results reveal the existence of complex small RNA-based regulatory networks mediating plant adaptation to mineral nutrient availability.

MiRs also regulate the adaptation of plants to abiotic stresses, including macronutrient limitations (Sunkar and Zhu, 2004; Fujii et al., 2005; Bari et al., 2006; Chiou et al., 2006; Sunkar et al., 2007). MiR395 and miR399 have been shown to be specifically induced during sulfur and phosphorus (P) limitation, respectively (Jones-Rhoades and Bartel, 2004; Fujii et al., 2005; Bari et al., 2006; Chiou et al., 2006; Kawashima et al., 2008). MiR399 targets the transcript of an E2-conjugase that is mutated in phosphate (Pi)-accumulating Arabidopsis (Arabidopsis thaliana) pho2 mutants, and this phenotype is recapitulated in miR399-overexpressing plants (Aung et al., 2006; Bari et al., 2006). MiR399 presumably acts in a dualistic manner to inhibit PHO2. It promotes transcript decay (Allen et al., 2005; Bari et al., 2006) but also appears to inhibit PHO2 expression by repressing translation (Bari et al., 2006), a mechanism that is probably widespread in plants (Aukerman and Sakai, 2003; Brodersen et al., 2008). Recently, miR167 has been associated with lateral root outgrowth in response to nitrogen (N) limitation (Gifford et al., 2008). Primary miR transcript 167a (pri-miR167a) was shown to be approximately 5-fold repressed by N in root pericycle cells, permitting the target ARF8 transcript to accumulate and initiate lateral root outgrowth. Furthermore, miR398 was reported to be down-regulated by oxidative stresses and copper limitation but induced by Suc, thereby repressing two copper/zinc (Cu/Zn) superoxide dismutases and a cytochrome c oxidase subunit (Sunkar et al., 2006; Yamasaki et al., 2007; Dugas and Bartel, 2008).

Despite these examples, little information about stress- or nutrient-responsive plant miRs is available. This is due to their often low expression levels and the absence of miR or MIRNA gene probes on widely used transcriptomics platforms such as Affymetrix GeneChips. Custom-made microarrays can be designed to include probes for miRs and MIRNA genes for a broader response analysis, but these are not very sensitive (Axtell and Bartel, 2005; Liu et al., 2008). Reverse transcription followed by quantitative PCR analysis (qRT-PCR) with nonspecific double-stranded DNA-binding fluorophores, such as SYBR Green, is a powerful alternative for highly sensitive, rapid, multiparallel, and cost-effective expression analysis (Udvardi et al., 2008). Shi and Chiang (2005) and Chen et al. (2005) reported two qRT-PCR-based methods to measure the levels of mature miRs. The first approach relies on in vitro polyadenylation of mature miRs followed by RT with an oligo(dT) adapter primer and amplification using SYBR Green with a miR-specific forward primer and a compatible reverse primer. In the second approach, each specific miR is reverse transcribed from total RNA using a specific stem-loop primer, followed by TaqMan PCR amplification. Although it is desirable to quantify the biologically active mature miR species, a limitation of both qRT-PCR methods is that they are unable to differentiate the expression strengths of MIRNA genes that yield (nearly) identical mature miR molecules. Hence, the interpretation of the results will be dominated by strongly expressed member(s) of a given MIRNA gene family, while the contribution of lowly expressed members will go unnoticed. This might be especially important if these genes are expressed in an organ- or cell type-specific manner.

Deep sequencing using new technologies (e.g. Illumina-Solexa chemistry) is another approach being adopted for the analysis of small RNA/miR abundance (German et al., 2008; Moxon et al., 2008a; Szittya et al., 2008). The high number of sequence reads promises sensitivity, yet the necessary expertise required and the labor and cost involved are considerable. Data from small RNA sequencing together with miR prediction algorithms like miRDeep (Friedländer et al., 2008) also provide the basis for the discovery of novel miRs, even in organisms that have been specifically surveyed to identify miRs.

We have developed a qRT-PCR platform for parallel analysis of 177 currently known Arabidopsis MIRNA gene pri-miRs. This platform provides a sensitive yet inexpensive tool for Arabidopsis researchers to carry out miR expression analysis. A comparable approach has previously been described for monitoring the expression of 23 human miR precursors (Schmittgen et al., 2004). As pri-miRs are generated by RNA polymerase II in plants and animals (Bracht et al., 2004; Cai et al., 2004; Kurihara and Watanabe, 2004; Lee et al., 2004), they contain 5# caps and 3# poly(A) tails. The latter make the transcripts amenable to oligo(dT)-primed RT and thus multiparallel analysis by qRT-PCR. Although pri-miRs are not the biologically active molecules, several previous studies have shown that the response of a pri-miR can reflect that of the encoded mature miR (Jones-Rhoades and Bartel, 2004; Bari et al., 2006; Pant et al., 2008) and thus can serve as a valid indicator. Therefore, qRT-PCR profiling of pri-miRs can serve as a useful tool to discover responses to particular stimuli, which can then be confirmed by analysis of the mature species.

In this work, we first established the pri-miR platform and then used it to discover previously unknown nutrient-responsive pri-miRs. The corresponding mature miRs were investigated by targeted assays and further confirmed by small RNA sequencing, which also revealed novel insights. The results indicate that small RNAs play a much more important role in nutrient signaling than previously thought.

	RESULTS

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 

A qRT-PCR Platform for Arabidopsis pri-miRs

Sequences of 184 annotated Arabidopsis miR stem loops were obtained from the miRBase database (www.microrna.sanger.ac.uk). These sequences are not strictly pre-miRs but may include flanking sequence from the presumed pri-miR. Pri-miR sequences of members from the same family can be almost identical, complicating the design of specific PCR primers. This occurs in the miR169 family, where miR169i through miR169n are located in three highly homologous, tandem-arrayed stretches (Supplemental Fig. S1), and in the miR854 family, where the pre-miR sequences of the four annotated members are 97% to 100% identical. However, it is questionable whether miR854s are true miRs, as the sequences are located close to (or in) the centromere of chromosome 5 and are annotated as transposable elements in The Arabidopsis Information Resource (TAIR) database (www.arabidopsis.org). Therefore, we treated miR854 as a single miR, leaving a total of 181 sequences for which primers were designed.

To ensure maximum specificity and efficiency during PCR amplification of pri-miR cDNA under a standard set of reaction conditions (Fig. 1A ), a stringent set of criteria was used for primer design (see "Materials and Methods"). PCR primers were tested on cDNA from Arabidopsis wild-type ecotype Columbia (Col-0) seedlings, which was free of genomic DNA contamination. Using this cDNA as template, 150 primer pairs gave unique PCR products of the expected size, while 27 primer pairs yielded no product and four gave unspecific products. The 27 primer pairs were retested using Arabidopsis Col-0 genomic DNA as template. Fifteen primer pairs resulted in the expected genomic product, showing that the primers anneal to the correct sequence and suggesting that the targeted pri-miRs (e.g. 159c, 166c, 395a to 395f, and 404; Supplemental File S2) were below the detection limit in the cDNA samples or that amplification from the cDNA was inhibited. Evidence in support of the former hypothesis comes from the observation that some of the primers (e.g. pri-miR395a to -395f) did amplify the expected products from a cDNA sample derived from sulfur-limited seedlings (Supplemental Fig. S2). The 16 primer pairs that did not yield any product from cDNA or genomic DNA templates, or that amplified unexpected/unspecific products, were redesigned, finally resulting in 175 validated primer pairs and only six MIRNA genes (highlighted in red in Supplemental File S2) for which no working pairs could be established.

View larger version (52K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 1. qRT-PCR platform for pri-miR transcript quantification. A, Typical real-time RT-PCR amplification plots of 175 miR amplicons showing increase in SYBR Green fluorescence (Rn; log scale) with PCR cycle number. Note the similar slope of most curves as they cross the fluorescence threshold of 0.18 (green line), which reflects similar amplification efficiency. B, Separation of PCR products on 4% (w/v) high-resolution agarose gels reveals single products of the expected size (black numbers). A selection of 10 amplicons is shown. Size standards in bp are indicated to the left. C, Distribution of efficiencies for 154 primer pairs (gray bars). For 21 primer pairs (white bar) no primer efficiencies were obtained in the conditions investigated. D, Expression strength distribution of MIRNA genes (white bars) and of transcription factor genes (black bars). Genes were grouped according to their CT values, calculated with UBQ10 as reference. [See online article for color version of this figure.]

The fraction of pri-miRs detected (i.e. expressed in at least two biological replicates with a threshold fluorescence cycle number [C_T] of less than 40) was just below 80%, irrespective of the growth conditions tested (Supplemental File S2). This percentage is comparable to the percentage of transcription factor (TF) genes detected at this threshold (approximately 83%; Czechowski et al., 2004). However, the average C_T value of pri-miRs was higher than for the TF gene transcripts (Fig. 1D). Hence, pri-miRs are often less abundant than TF transcripts. Low abundance (C_T > 33) also resulted in higher variability between replicate measurements, making detection of small expression changes less reliable.

Identification of N- and P-Responsive Arabidopsis pri-miRs

The qRT-PCR platform was used to identify pri-miRs that are induced or repressed in 9-d-old Arabidopsis seedlings during N or P limitation (Supplemental File S2). The expected physiological status of the seedlings was confirmed by evaluation of marker gene expression (Supplemental Fig. S5). NRT2.5 (At1g12940) and AMT1.5 (At3g24290) were both strongly induced in N-limited seedlings, and PHT1.4 (At2g38940) was induced by P limitation, as found previously (Scheible et al., 2004; Morcuende et al., 2007).

Twenty pri-miRs exhibited differential expression in N- or P-limited conditions (Fig. 2 ), based on an average change in normalized cycle number of at least three (|C_T| $ 3) between nutrient limitation and full nutrition (FN). The most prominent change was the known induction of pri-miR399s during P limitation, with C_T ranging from 6.5 to 20 (Fig. 2; Bari et al., 2006). Pri-miR399d was undetectable in FN conditions and rose to levels comparable to some of the most strongly expressed genes in Arabidopsis, such as UBQ10 (Czechowski et al., 2005). Very high expression of pri-miR399s and mature miR399 during P limitation is necessary to fully suppress the activity of its target PHO2 transcript (Bari et al., 2006). Mechanistically, this seems to involve translational repression, as suggested by previous results (Bari et al., 2006) and our finding that miR399d-overexpressing seedlings have substantially lower but still detectable levels of PHO2 transcript (10%–20% of control plants), while their molecular phenotypes are identical to pho2 seedlings (Supplemental Fig. S6).

View larger version (22K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 2. Identification of N/P limitation-responsive pri-miRs in Arabidopsis. For each pri-miR species, the average CT value ± SE from three biological replicates (with two technical replicates for each) is depicted. CT = CT FN – CT -nutrient, and CT = CT pri-miR – CT UBQ10. Pri-miRs induced in nutrient limitation thus have a positive CT value and vice versa. The fold induction can be inferred from the equation (1 + E)CT, where E is PCR efficiency (Supplemental File S2). Only pri-miRs with average CT values of >3 or <–3 (as indicated by the light gray shading) are shown. Results for P and N limitation are shown as dark gray and white bars, respectively.

Pri-miR398a and pri-miR447c were not only responsive to P limitation but also showed similar responses in N limitation, albeit not as strong, with pri-miR398a being slightly repressed (C_T = –2.45; Supplemental File S2) and pri-miR447c induced (C_T = 3.5; Fig. 2). Furthermore, pri-miRs156e, -156g, and -157d were found to be induced (C_T = 3.1–4.4) in N-limited seedlings. Pri-miR167a, which was reported to be more highly expressed in N-limited root pericycle cells (Gifford et al., 2008), showed no clear response in our experiments with N-limited seedlings. However, pri-miR167d was less expressed (C_T = –2.5) in N-limited seedlings (Supplemental File S2).

Nutrient-Responsive Mature miR Species

To examine if the mature miRs derived from the nutrient-responsive pri-miRs also showed a nutrient response, we used a qRT-PCR approach similar to the one described by Chen et al. (2005; Supplemental Table S1). In addition to nutrient-replete (FN), N-limited (–N), and P-limited (–P) Arabidopsis seedlings, we also included carbohydrate-limited (–C) seedlings (Supplemental Fig. S5) in the analysis. Mature miR399s were not analyzed, since their high abundance during P limitation is already well documented (see introduction).

MiR778 and miR827 were both strongly induced by P limitation, thus confirming the response of their pri-miRs. However, they did not respond to either N or C limitation (Fig. 3 ) and remained almost undetectable under these conditions, suggesting that both of these miRs are involved in P-specific regulation events. The response of miR398a was also similar to that of the corresponding pri-miR, being decreased by P and N limitation and also by C limitation (Fig. 3).

View larger version (46K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 3. Nutrient responsiveness of mature miRs. qRT-PCR results are shown for nutrient-replete (white bars), P-limited (black bars), N-limited (gray bars), and C-limited (hatched bars) Arabidopsis seedlings. Expression levels are given on a logarithmic scale expressed as 40 – CT, where CT is the difference in qRT-PCR threshold cycle number of the respective miR and the reference gene UBQ10 (At4g05320); therefore, 40 equals the expression level of UBQ10 (the number 40 was chosen because the PCR run stops after 40 cycles). The results are averages ± SE of three biological replicates. Significance of the changes found during P, N, or C limitation was checked with Student's t test. P < 0.05 is indicated by circles, and P < 0.01 is indicated by plus signs.

Nucleolytic cleavage of pri-miR169h to -n (Supplemental Fig. S1) by the DICER endoribonuclease results in identical miR169 molecules, precluding a specific assay. Nonetheless, since all seven pri-miR sequences were less abundant in N limitation (Fig. 2), we were able to confirm lower miR169h to -n levels in N limitation (Fig. 3). The moderate induction found for two of these pri-miR169 species during P limitation was not supported by the miR169h to -n assay; on the contrary, mature miR169h to -n showed a significant (approximately 3-fold) decrease in P limitation. A second assay designed for miR169a to -g also indicated lower abundance during N and P limitation (Fig. 3), although no clear change was detected for the corresponding pri-miRs.

We were also able to confirm a slight induction (C_T 2) of miR447 during P but not N limitation, whereas the induction of miR156 during N limitation, as suggested by pri-miR156e and -156g (Fig. 2), was not confirmed (Fig. 3). Again, a nonspecific assay and high expression of other pri-miRs from the same family (Supplemental File S2) probably account for this discrepancy.

P Status-Responsive miRs Detected by Small RNA Sequencing

As an independent approach to verify the P responsiveness of mature miRs, we used small RNA sequencing (SRS) with Illumina-Solexa technology. Three cDNA libraries prepared from nutrient-replete (FN) seedlings, P-limited (–P) seedlings, and –P seedlings that were resupplied with 3 mM phosphate for 3 h were sequenced (Supplemental Table S2). Sequence reads with 100% identity to Arabidopsis pre-miRs were extracted, and identical reads were totaled (Supplemental Table S2; Supplemental Fig. S7; Supplemental File S3) and normalized for each library. A plot of the distribution of read lengths for pre-miR-matching sequences (Supplemental Fig. S7A) illustrates that these consist almost exclusively of 20- and 21-mers, with the latter being the most abundant, whereas a plot of all genome-matching sequences reveals a substantial number of 24-mers and other lengths (Supplemental Fig. S7B). Comparison also shows a significantly (approximately 30%) higher number of 21-mers in the group of genome-matching sequences, possibly indicating the presence of unknown miRs.

The normalized read numbers for miR399s were high during P limitation and very low in nutrient-replete (FN) conditions (Fig. 4A ), as expected (Bari et al., 2006; Pant et al., 2008). There was no appreciable decrease of miR399s at 3 h after Pi readdition, supporting earlier results that suggested that miR399s are rather stable (Bari et al., 2006). SRS also confirmed high expression of miR778 and miR827 during P limitation (Fig. 4A). Very few (one or two) or no reads were obtained for miR398a, -447c, -845, or -169h to -n, whereas these miRs were detectable by qRT-PCR, suggesting that our qRT-PCR analysis was more sensitive than the SRS approach. SRS showed three additional miRs (i.e. miR408, miR829, and miR863) to be 4- to 10-fold more abundant during P limitation. Analysis by qRT-PCR supported the increase in levels of miR408 but was unable to confirm the higher abundance of miR829 or miR863 (Supplemental Fig. S8).

View larger version (49K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 4. P-responsive miRs as detected by small RNA sequencing. A, The number of normalized sequence reads (ppm) is shown for all miRs and their corresponding star (*) strands that show at least a 5-fold change between P limitation (black bars) and P-replete (white bars) conditions and for which at least 10 total reads were scored in at least one condition (Supplemental File S3). Normalized read numbers are also shown for a time point of 3 h after resupply of 3 mM potassium phosphate to previously P-limited seedlings (3hP; gray bars). Missing bars indicate zero reads. B, Putative miR2111a and -b precursor sequences and structures. The sequences of mature miR2111 and the presumed star strands are shown in boldface on the top and bottom strands, respectively. The number of absolute reads for the three conditions tested (see A) is indicated. C, qRT-PCR expression of the 82- and 103-nucleotide-long pri-miR2111a and -b amplicons in various conditions (FN, full nutrients; –P, P limitation; 3hP, 3 h of Pi readdition; –N, N limitation; –C, carbohydrate limitation). Expression levels are plotted on a logarithmic scale as described in the legend to Figure 3. The results are averages ± SE of three biological replicates with two technical replicates for each.

Discovery of a Novel P Status-Responsive miR

The SRS data were analyzed further to look for novel P status-dependent miRs. Candidate miRs were predicted using a miRDeep algorithm (Friedländer et al., 2008) that was adapted for plant miR precursor sequences (P. May and M. Friedländer, unpublished data). Among the predicted miR candidates was one, named miR2111, that showed a very strong dependence on P status (Fig. 4A). It is highly abundant during P limitation but almost absent in nutrient-replete seedlings and so closely resembles the behavior of known P-responsive miRs (miR399s, miR778, and miR827) in these conditions. When Pi is resupplied to Pi-limited seedlings, the abundance of the novel miR2111 fell by approximately 2-fold within 3 h of Pi readdition (Fig. 4A). This response differs from those of miR399s and miR827, which do not fall rapidly after Pi readdition, but is similar to that of miR778, suggesting that the biological half-lives of miRs can vary considerably.

The DNA sequence of miR2111 is present twice in the Arabidopsis genome: upstream of At5g02040, and between At3g09280 and At3g09290. For these locations, the algorithms miRDeep and miRCat (http://srna-tools.cmp.uea.ac.uk) predicted two precursor sequences/structures, named pre-miR2111a and -b (Fig. 4B). The observation that the read numbers of the two star strands (miR2111a* and miR2111b*) are similar and that they decrease after Pi readdition or are almost absent in P-replete conditions reveals that both loci have P-responsive expression and contribute to a similar extent. The strong P limitation response of miR2111 was confirmed by qRT-PCR (Supplemental Fig. S8). In addition, PCR products designed to encompass larger stretches (82 and 103 nucleotides) of pre-miR2111a and -b could be amplified from oligo(dT)-primed cDNA pools, showing that miR2111 is derived from poly(A)-tailed primary transcripts, and these also displayed strong P responsiveness (Fig. 4C). Furthermore, both the mature miR2111 and its pri-miRs displayed specificity for P, as N or C limitation did not affect the expression levels (Fig. 4C; Supplemental Fig. S8). We were also able to find potential orthologs of pre-miR2111s in rapeseed (Brassica napus; Supplemental Fig. S9). The rapeseed 2111a and 2111b precursors share 85% and 83% identity at the DNA level with their Arabidopsis counterparts and are predicted to fold into stable extended hairpin structures by the miRCat algorithm. PCR primer pairs for Arabidopsis pri-miR2111a and -2111b were added to the qRT-PCR platform, thus bringing the number of MIRNA genes represented to 177 (Supplemental File S2).

MiRs with P or N Status-Dependent Abundance in Rapeseed Phloem Sap

MiR399 was previously found to be highly abundant in phloem sap from rapeseed and pumpkin (Cucurbita maxima) during P limitation and to constitute a shoot-derived long-distance signal for the regulation of plant Pi homeostasis (Buhtz et al., 2008; Lin et al., 2008; Pant et al., 2008). To test whether additional miRs show nutrient status-dependent abundance in phloem sap, we collected sap from nutrient-replete, P-limited, and N-limited rapeseed plants and prepared small RNA libraries for sequencing.

Analysis of the resulting small RNA reads (Supplemental Table S3) showed that sequences homologous to miRs known to be present in the phloem (e.g. miR156, miR159, and miR167) were present in the libraries, whereas sequences homologous to miR171, which is abundant in leaf or stem tissue but undetectable in phloem (Yoo et al., 2004; Buhtz et al., 2008), were completely absent (Fig. 5A ). This indicates that the phloem sap samples were not noticeably contaminated with small RNAs from stem tissue. Small RNA species found in the libraries should thus represent authentic phloem constituents. The high purity of rapeseed phloem sap obtained using the same method was previously reported by Giavalisco et al. (2006) and Buhtz et al. (2008).

View larger version (26K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 5. miRs with P or N status-dependent abundance in rapeseed phloem sap. A, Abundance of miRs known to be present (miR156, miR159, and miR167) or absent (miR171) in rapeseed phloem sap. B, MiR and miR* sequences with P or N status-dependent abundance. Depicted are normalized read numbers as detected by Solexa sequencing in small RNA libraries prepared from phloem sap samples of P-starved (black bars), nutrient-replete (white bars), and N-starved (gray bars) rapeseed plants. The significance of the changes between P-starved (or N-starved) and nutrient-replete conditions was analyzed with a 2 test and Benjamini-Hochberg P value correction; P < 0.0003 is marked with circles. Sequences of the species shown are as follows: 169m, 5#-TGAGCCAAAGATGACTTGCCG-3#; 399, 5#-TGCCAAAGGAGATTTGCCCGG-3#; 399-like, 5#-TGCCAAAGGAGATTTGTCCGG-3#; 399*-like 1, 5#-GGGCGAATACTCTTATGGCAGA-3#; 399*-like 2, 5#-GGGCAAGATCTCTATTGGCAGA-3#; 2111, 5#-TAATCTGCATCCTGAGGTTTA-3#; 2111-like, 5#-TAATCGGCATCCTGAGGTTTA-3#; 2111a*, 5#-ATCCTCGGGATACAGATTACC-3#; 2111b*, 5#-GTCCTCGGGATGCGGATTACC-3#; 2111*-like 1, 5#-ATCCTCGGGATGCGGATTACC-3#; 2111*-like 2, 5#-ATCCTCGGGATACGGATTACC-3#; 2111*-like 3, 5#-ATCCTCGGGACACAGATTACC-3#; 2111*-like 4, 5#-GACCTCAGGATGCGGATTACC-3#; 2111*-like 5, 5#-TCCTCGGGATACAGATTACC-3#; 156, 5#-TGACAGAAGAGAGTGAGCAC-3#; 159, 5#-TTTGGATTGAAGGGAGCTCTA-3#; 167, 5#-TGAAGCTGCCAGCATGATCTA-3#; 171, 5#-TGATTGAGCCGCGCCAATATC-3#.

Target Predictions for Nutrient-Regulated miRs

To identify candidate miR target genes, we used four prediction algorithms: miRU (Zhang, 2005), target search in WMD2 (Ossowski et al., 2008), the prediction tool in the UEA plant sRNA toolkit (Moxon et al., 2008b), and PITA (Kertesz et al., 2007). In addition, we mined experimental data from degradome studies (Addo-Quaye et al., 2008; German et al., 2008). The first three algorithms score the complementarity of miR and target RNA sequences based on established rules (e.g. the "seed rule"; Allen et al., 2005), thereby also exploring the observation that plant miRs seem to bind almost perfectly to their cognate mRNAs (Rhoades et al., 2002; Lai, 2004). In contrast, PITA assesses site accessibility in miR target recognition. This includes prediction of target RNA secondary structure and calculation of the free energy gained from the formation of the miR-target duplex and the energetic cost of unpairing the target to make it accessible to the miR. All candidate miR targets predicted with miRU, WMD2, or the UEA plant sRNA toolkit, and up to 20 best targets from the PITA analysis, are shown in Supplemental File S4, with a selection of the predicted targets shown in Table I.

Obvious targets of miR827 are the E3 ligase gene NLA (At1g02860) and its homolog At1g63010 (Table I; Fahlgren et al., 2007). Also, miR2111 is predicted to target an E3 ligase gene (At3g27150) and a calcineurin-like phosphoesterase gene (At1g07010). A likely target of miR778 is the histone methyltransferase gene SUVH6 (At2g22740), with SUVH5 (At2g35160) being a possible target as well. Interestingly, miR2111a* and miR2111b* also appear to target genes required for chromatin remodeling/modification (i.e. At2g23380/CURLY LEAF and At2g28290/SPLAYED).

Confirmed targets of miR398a include two Cu/Zn superoxide dismutase genes (CSD1 and CSD2) and COX5b.1 (see introduction). The prediction algorithms detected CSD1, COX5b.1, and At1g12520/CCS1, a chaperone that activates CSD, as potential targets of miR398a (Table I). CSD2 was not found, most likely due to a bulge and GU wobble in the seed region of the CSD2 miR398a duplex (Brodersen and Voinnet, 2009).

	DISCUSSION

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 

qRT-PCR of pri-miRs Is Suitable for Discovery of Stimulus-Dependent miRs

The role of miRs during the adaptation of plants to abiotic and nutritional stresses is a field that attracts increasing interest (Chiou, 2007; Sunkar et al., 2007), but information on stress-dependent expression of MIRNA genes is limited. To overcome this situation, we developed a qRT-PCR platform for quantification of almost all known Arabidopsis pri-miRs. The results obtained with the platform and from targeted assays for mature miRs show that the responses of pri-miRs frequently match the responses of the biologically active mature species, thus validating pri-miR profiling as a useful discovery tool. It is also rapid, sensitive, and inexpensive and should represent an attractive initial approach for the investigation of MIRNA gene expression. The usefulness of the pri-miR platform is also demonstrated by comparative analysis of the hyl1 mutant and wild-type plants, revealing accumulation of specific pri-miRs in hyl1 and thus an important role for the HYL1 double-stranded RNA-binding protein in selective pri-miR maturation (Szarzynska et al., 2009). We found only a few examples where the P or N response of pri-miRs was not confirmed for the corresponding mature miRs. Although this could have been due to technical reasons, regulation or attenuation at the level of miR maturation could also account for these differences.

It is likely that the number of recognized Arabidopsis MIRNA loci will further increase (Lindow and Krogh, 2005; Lindow et al., 2007), especially with deeper analysis of SRS data, possibly reaching numbers similar to those currently known for rice (Oryza sativa; 269), zebra fish (337), mouse (472), and human (678; http://microrna.sanger.ac.uk). The easily scalable qRT-PCR approach allows regular updates of the platform as new MIRNA genes are discovered. In this regard, we invite readers to send us relevant sequence information.

Evidence for miR2111 Being a True miR

The novel Pi-responsive miR2111 was revealed by a version of miRDeep optimized for analysis of plant sequences (P. May, unpublished data), but this alone is not conclusive proof that it is a true miR. A number of revised criteria exist for annotation of plant miRs (Meyers et al., 2008). The primary and only criterion that is necessary and sufficient for annotation as a miR is conclusive evidence of precise biogenesis from a qualifying stem loop, and this criterion is met by miR2111. First, miR2111 was shown to be derived from longer poly(A)-tailed precursor transcripts, as it was possible to obtain precursor PCR amplicons from cDNA pools generated by RT with an oligo(dT) primer (Fig. 4C). Second, the two miR2111 precursors fold into characteristic hairpin structures with stabilities typical for known miR precursors. Third, there is precise excision of 21-nucleotide miR2111/miR2111* duplexes from the two stem-loop precursors (Supplemental File S3). Fourth, miR2111 and miR2111a/b* are derived from opposite stem arms and form duplexes with typical 3# overhangs of two-nucleotide length. Fifth, base pairing between miR2111 and the star strands is extensive (Fig. 4B). Finally, the observed small RNA abundance corresponds entirely to the duplexes. Ancillary criteria for plant miR annotation include (1) the existence of target genes, (2) conservation between species, and (3) biogenesis that is dependent on DICER-like (DCL) proteins. There are obvious potential target genes for miR2111 (Table I), although the biological significance of these being targeted by miR2111 is as yet unknown. We also detected pre-miR2111 homologs and found mature miR2111 in rapeseed (Fig. 5; Supplemental Fig. S9). Although the dependence of miR2111 biogenesis on DCL1 or DCL4 still needs to be tested, there is already overwhelming evidence that miR2111 is a true miR.

More Widespread Regulation by Small RNAs during P Limitation

So far, miR399s have been the only small RNA species known to strongly increase during P limitation (see introduction). Five MIRNA399 genes that encode the slightly different mature miR399s exist in Arabidopsis. Still the only confirmed target of miR399s is PHO2, while IPS1 is a miR399 interactor (Franco-Zorrilla et al., 2007). This situation and expansion of the MIRNA399 gene family in other plant species such as Medicago truncatula (F. Krajinski, personal communication) and rice (Lindow et al., 2007), however, indicate a larger miR399 regulatory network. The new finding that at least four additional miRs and several miR*s with strong P status-dependent expression exist now suggests that regulation/signaling by small RNAs during P limitation is even more widespread. Regulatory activity of miR* species and their presence in argonaute complexes have been demonstrated previously (Mi et al., 2008; Okamura et al., 2008). The fact that the SRS read numbers for some miR* sequences clearly exceed the numbers for the corresponding miRs indicates that they are not merely by-products that are slowly degraded.

Target Predictions and Biological Processes Potentially Affected by P-Regulated Small RNAs

We used several prediction algorithms and mined degradome data (Table I) to determine likely targets of P-regulated small RNAs. This combinatorial approach revealed several miR targets that were predicted by two or more complementary algorithms, giving greater confidence in the predictions. Target analysis with PITA also indicated that inclusion of thermodynamics of RNA-RNA interactions can change the results greatly (Hofacker, 2007). Only PITA correctly identified IPS1, a noncoding RNA that qualifies as a bona fide miR399 target-like interactor (Franco-Zorrilla et al., 2007), emphasizing the complementarity and predictive power of PITA. The number of potential targets identified with PITA (Supplemental File S4) further suggests that an individual plant miR could also have a larger range of action, for example, by inducing widespread changes in protein synthesis, as recently reported for several human miRs (Selbach et al., 2008).

Three P starvation-inducible miRs (miR399, miR2111, and miR827) have confirmed or likely target genes involved in protein degradation via the 26S proteasome. MiR827 targets the E3 ligase gene NLA (At1g02860). NLA transcript also drops 2- to 3-fold during P limitation when miR827 is highly expressed (Morcuende et al., 2007). NLA is crucial for anthocyanin synthesis, and the nla mutant displays severely reduced anthocyanin content and early leaf senescence during N limitation (Peng et al., 2007a, 2007b, 2008). However, during P limitation or during simultaneous P and N limitation, the mutant displays wild-type-like anthocyanin levels and no leaf senescence (Peng et al., 2008), showing that the signal derived from P limitation is sufficient to induce anthocyanin production in the nla mutant. The link between P limitation and NLA provided by miR827 (Fig. 6A ) suggests that NLA activity is actively down-regulated during P limitation. This could indicate that plants select one or the other input signal depending on nutrient conditions and, therefore, the existence of hierarchies in the interplay of macronutrient regulatory networks. MiR2111 is predicted to target the E3 ligase gene At3g27150 (Table I). At3g27150 displays strictly root-specific expression in large-scale transcriptome data sets like AtGenExpress (Schmid et al., 2005), suggesting that it functions in the root. This is interesting in the context of the high abundance of miR2111 in phloem sap during Pi limitation (Fig. 5), suggesting another systemic regulatory circuitry, analogous to the miR399-PHO2 paradigm (Pant et al., 2008).

View larger version (16K): [in this window] [in a new window] [as a PowerPoint slide]   Figure 6. Hypothetical models for miR827 and miR169 functions. A, Model showing cross talk between P limitation and N limitation signaling pathways that affect anthocyanin synthesis. B, Model integrating published features of the systemic regulation of nodulation by CLE (Okamoto et al., 2009), SUNN/HAR1 (Krusell et al., 2002), and HAP2 and miR169 (Combier et al., 2006), with novel results concerning miR169 described in this work.

MiR398a is strongly reduced in P, N, and C limitation (Fig. 3), indicating a more general response to nutrient stress. Repression of miR398a by C limitation also correlates with its induction by Suc (Dugas and Bartel, 2008). Targets of miR398a include CSD1 and CSD2 (see introduction). CSD is required for detoxification of reactive oxygen species that increase during nutrient limitations and other environmental stresses (e.g. heat or drought; Apel and Hirt, 2004; Shin et al., 2005; Sunkar et al., 2006). Therefore, down-regulation of miR398a leading to higher CSD activity would be an appropriate response to nutrient stress.

Potential Biological Impact of miR169 Regulation by N Availability

The targets of miR169s are several HAP2 transcription factors (i.e. nuclear factor YA subunits [NF-YA]; Table I; Combier et al., 2006; Fahlgren et al., 2007; Li et al., 2008). Transcripts of several of these genes, including At3g05690/NF-YA2, At1g54160/NF-YA5, At3g14020/NF-YA6, At1g72830/NF-YA8, and At5g06510/NF-YA10, increase during N and P limitation (Supplemental Fig. S10; Scheible et al., 2004; qRT-PCR confirmation not shown), thereby showing the opposite response compared with miR169.

In Arabidopsis, miR169 was reported to influence drought resistance via inhibition of the A5 subunit of NF-Y, a ubiquitous transcription factor that is highly expressed in guard cells and crucial for the expression of a number of drought stress-responsive genes (Li et al., 2008). Nfya5 knockout mutants and plants overexpressing miR169 show enhanced leaf water loss and are more sensitive to drought stress, whereas NFYA5 overexpressers show the opposite phenotypes (Li et al., 2008). In addition to the effects of the nitrate transporter CHL1 (Guo et al., 2003) or nitrate reductase-mediated nitric oxide generation (Desikan et al., 2002) on stomatal opening, low expression of miR169 during N limitation could thus contribute to drought tolerance of N-limited plants (Lodeiro et al., 2000; Castaings et al., 2008).

In legume species, nodule development is dependent on the presence of previously established nodules and N/nitrate availability, creating a root-to-shoot signal that activates the CLAVATA1-like receptor kinase SUNN in M. truncatula or HAR1 in Lotus japonicus. A recent report suggests that a nitrate-induced CLAVATA3/ESR-related (CLE) peptide is this root-to-shoot signal (Fig. 6B; Okamoto et al., 2009). HAR1 exerts negative shoot control of root nodulation (Krusell et al., 2002; Nishimura et al., 2002) through a shoot-to-root signal that might include auxin transport (van Noorden et al., 2006). It is also known that the miR169 target gene HAP2-1 in M. truncatula is a key regulator for the differentiation of nodule primordia (Combier et al., 2006; Fig. 6B). MiR169 overexpression or knockdown of HAP2-1 leads to a developmental block of nodule formation (Combier et al., 2006). Repression of miR169s by N limitation, as detected in our experiments, points toward a potential mechanistic link between low N status and nodule development in legumes. High abundance of miR169 in phloem sap during N-replete growth and the sharp decrease during N and P limitation (Fig. 5) also flags miR169 as a potential long-distance signal (Fig. 6B) that is able to report shoot N and P status to the roots, similar to the role of miR399 (Pant et al., 2008). It will be interesting to test whether miR169 abundance is increased by nitrate/N in legumes and whether miR169 expression and/or phloem abundance is dependent on SUNN/HAR1 to establish if this is a novel shoot-to-root signal for the control of nodule differentiation.

	CONCLUSION

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 
MiRs are emerging as increasingly interesting (systemic) regulators during mineral nutrient stress in plants. The discovery of new nutrient-dependent miRs opens up the possibility of testing their roles and those of their predicted targets during adaptation of plants to nutrient deficiency. The qRT-PCR platform described here serves as a useful initial approach to test the response of annotated miRs in a given biological scenario, providing opportunities to discover new signaling and regulatory networks.

	MATERIALS AND METHODS

TOP ABSTRACT RESULTS DISCUSSION CONCLUSION MATERIALS AND METHODS LITERATURE CITED

 

Plant Materials

Nine-day-old nutrient-replete and N-, P-, or C-limited wild-type Arabidopsis (Arabidopsis thaliana Col-0) seedlings were grown in sterile liquid cultures as described previously (Scheible et al., 2004; Morcuende et al., 2007; Osuna et al., 2007). The physiological status of the plant materials was confirmed by expression analysis of marker genes (Supplemental Fig. S5) prior to qRT-PCR analysis. Rapeseed (Brassica napus ‘Drakkar’) was germinated and grown hydroponically (Buhtz et al., 2008) in a full-nutrient solution containing 4 mM N and 0.5 mM P. After 47 d, plants were divided into three sets, and one set was supplied with lower N (2 mM KNO₃) nutrient solution, one with low P (0.1 M KPi) nutrient solution, and one with full-nutrient solution. From day 61 onward (i.e. approximately 1 week before flowering started), low-N, low-P, and FN plants were supplied with nutrient solutions containing no N, no P, or full-nutrient solution, respectively. N- or P-limited plants developed clear signs of N or P starvation (e.g. reduced leaf biomass, earlier flowering, reduced chlorophyll in –N leaves; data not shown). Phloem sap was sampled between days 72 and 82 as described previously and was not significantly contaminated by cell sap from other tissues (Giavalisco et al., 2006; Buhtz et al., 2008).

Primer Design and qRT-PCR Analysis

A first set of pri-miR primers (pri-miR156 through -404) was designed by Eurogentec. Primers for pri-miR405 through -870, and primers that replaced malfunctioning primers from the first set were designed using Primer Express 2.0.0 (Applied Biosystems) and Oligo 6.71 (Molecular Biology Insights). To ensure maximum specificity and efficiency during PCR amplification of pri-miR cDNA under a standard set of reaction conditions (Fig. 1A), a stringent set of criteria was used for primer design. This included predicted melting temperatures of 61°C ± 2°C, limited self-complementarity, and PCR amplicon lengths of 50 to 150 bp. Secondary hits were minimized by aligning primer candidates to all known Arabidopsis transcript sequences via BLAST searches and eliminating primer pairs with more than the specific hit. Stem-loop sequences for which no satisfactory primers could be found were elongated by 100 bp of flanking genomic sequence on each side before primer design was reinitiated. Annealing sites of the primers on the pri-miR sequence are highlighted in Supplemental File S1. Sequences of the qRT-PCR primers are given in Supplemental File S2. Cartridge-purified primers were purchased from Eurogentec, mixed with the corresponding forward or reverse primer upon arrival to a final concentration of 50 µM each, arrayed on 96-deep-well plates, and frozen at –80°C for long-term storage. Working stocks (0.5 µM) of each primer pair were prepared from the storage stocks in two serial 10-fold dilution steps and kept at –20°C for short-term storage and used within 2 weeks.

RNA isolation, cDNA synthesis, and qRT-PCR analysis were carried out as described previously by Czechowski et al. (2004, 2005) and Udvardi et al. (2008). Mature miR expression was analyzed using the method of Chen et al. (2005), as described (Pant et al., 2008). MiR-specific RT stem-loop primers are given in Supplemental Table S1. Primer sequences for marker genes are given in the legend to Supplemental Figure S5.

Isolation of Small RNAs, Library Preparation, and Deep Sequencing

Total RNA was isolated with Trizol reagent (Invitrogen) supplemented with 0.5% (w/v) N-lauroylsarcosine sodium salt, 3 mM β-mercaptoethanol, and 5 mM EDTA. After phase separation, one phenol/chloroform and two chloroform extractions were performed. The aqueous phase (500 µL) was mixed with 3 µL of glycogen (Roche; 20 mg mL^–1) before RNA was precipitated with 625 µL of ethanol and 250 µL of 0.8 M sodium citrate/1.2 M sodium chloride. Samples were incubated for 30 min at room temperature and then centrifuged (25 min, 16,000g, 4°C). The precipitate was washed with 80% (v/v) ethanol, air dried, and dissolved in 2 mM Tris-HCl (pH 7.5). Efficiency of small RNA extraction and total RNA quality was checked by northern-blot hybridization with a ³²P-labeled oligonucleotide complementary to miR399 (Bari et al., 2006). RNA concentration was measured with a NanoDrop ND-1000 (NanoDrop Technologies), and integrity was measured with an Agilent-2100 Bioanalyzer (Agilent Technologies; RNA 6000 NanoChips).

Total RNA from three independent biological replicates (3 x 20 µg) was mixed with 2x loading buffer II (Ambion), denatured for 2 min at 90°C, and separated on a 15% polyacrylamide/7 M urea/1x TBE gel at 300 V. Synthetic, phosphorylated 18-mer and 24-mer RNA markers (Biomers.net) and a 10-bp DNA ladder (Invitrogen) were used to localize small RNAs (18–30 nucleotides) as well as ligation and PCR products on gels stained with SYBR Gold (Invitrogen). RNA and PCR products were eluted from polyacrylamide gels in 300 µL of EBR buffer (50 mM Mg acetate, 0.5 M ammonium acetate, 1 mM EDTA, and 0.1% SDS) for 10 to 16 h at 20°C to 25°C (300 rpm). After phenol/chloroform and chloroform extraction, the aqueous phase was mixed with 1 µL of glycogen and 900 µL of 96% (v/v) ethanol, then cooled to –20°C for 2 h and centrifuged (25 min, 16,000g, 4°C). The RNA pellet was washed twice with 75% (v/v) ethanol and dissolved in 6 µL of water.

5# and 3# RNA adaptor ligations with RNA primers, RT, and PCR were performed according to Lu et al. (2007), except for a 3# RNA adaptor 3# end modification consisting of a C3 hydrocarbon spacer (Biomers.net). The PCR (25 µL) was terminated with 75 µL of stop buffer (10 mM Tris-HCl, pH 8.0, 1 mM EDTA, and 0.4 M ammonium acetate). After phenol (pH = 8.0)/chloroform extraction, 1 µL of glycogen (Roche; 20 mg mL^–1) and 300 µL of ethanol were added to precipitate cDNA. The cDNA was denatured in loading buffer II (Ambion) and separated on an 8% polyacrylamide/7 M urea gel. The cDNA band was eluted and precipitated as above. The pellet was washed with 70% (v/v) ethanol, air dried, and dissolved in 14 µL of water. The cDNA concentration was measured using a NanoDrop ND-1000 and checked by 15% polyacrylamide/7 M urea gel electrophoresis with oligonucleotides of known concentration. Quality control was performed by TOPO cloning and Sanger sequencing of several plasmid clones (Lu et al., 2007). Illumina-Solexa sequencing was performed at GATC Biotech for Arabidopsis and at FASTERIS for rapeseed libraries.

Analysis of Deep Sequencing Results

Sequencing reads of lengths between 15 and 32 nucleotides were used after trimming sequence adapters and low-complexity regions [e.g. poly(A)] and after removing reads of low quality (containing n runs, where n > 12). The read sets from the different conditions were subsequently mapped onto the Arabidopsis genome (TAIR8 assembly) using RazerS software. RazerS is an efficient and generic read-mapping tool allowing the user to align reads of arbitrary length using either the Hamming distance or the edit distance. RazerS is part of the generic sequence analysis library Seqan (Doring et al., 2008). Only perfect matches to the genome (i.e. full-length alignments with 100% identity) were retained. To investigate the read distributions for available TAIR8 annotations of genes and transposable elements (available from ftp://ftp.arabidopsis.org/home/tair/Genes/TAIR8_genome_release) and to find statistically significant changes in read distributions, we used the ² test together with Benjamini-Hochberg P value correction. The ² test is known to have a good predictive power and robustness for gene expression analysis (Man et al., 2000). Normalization of small RNA data was performed by dividing the read number of each individual small RNA sequence by the number of redundant reads (15–32 nucleotides) in each library (Supplemental Tables S2 and S3).

MiR Prediction

Potential miRs together with their precursor sequences were predicted using the miRDeep software tool (Friedländer et al., 2008). The miRDeep algorithm was adjusted to plant precursor structures to take account of the following features of some plant miRs: (1) longer pre-miRs; (2) pre-miRs that contain more than one miR sequence; (3) the more diverse read distribution of sequenced small RNAs on plant pre-miR sequences; and (4) nonhairpin pre-miR structures (P. May, unpublished data).

Target Gene Predictions

Candidate miR target genes were determined using publicly available prediction algorithms, including miRU (Zhang, 2005), the target search in WMD2 (Ossowski et al., 2008), the prediction tool in the UEA plant sRNA toolkit (Moxon et al., 2008b), and PITA (Kertesz et al., 2007). The programs were used with their default settings.

MiRBase accession numbers for all annotated Arabidopsis miRs are available at http://microrna.sanger.ac.uk/cgi-bin/sequences/mirna_summary.pl?org=ath. GenBank accession numbers for the novel miR2111 sequences described in this work are FN391952 (Ath-miR2111b), FN391950 (Ath-miR2111a), FN391951 (Bna-miR2111b), and FN391953 (Bna-miR2111a).

Supplemental Data

The following materials are available in the online version of this article.

Supplemental Figure S1. Genome arrangement and sequence similarity of miR169i to -n precursors.

Supplemental Figure S2. Strong induction of mir395 primary transcripts during sulfur limitation.

Supplemental Figure S3. Melting curves of pri-miR amplicons

Supplemental Figure S4. Sequencing results of four pri-miR amplicons.

Supplemental Figure S5. Marker gene expression in nutrient-limited Arabidopsis seedlings.

Supplemental Figure S6. Strong overexpression of miR399d mimics molecular phenotypes of pho2 mutants.

Supplemental Figure S7. Number and length distribution of small RNA sequences.

Supplemental Figure S8. qRT-PCR verification of P limitation-induced small RNA species.

Supplemental Figure S9. miR2111 precursors from rapeseed.

Supplemental Figure S10. Nutrient-dependent expression of HAP2 genes in Arabidopsis.

Supplemental Table S1. Primers used for RT of mature miR and qPCR quantification.

Supplemental Table S2. Read numbers from small RNA sequencing of Arabidopsis libraries.

Supplemental Table S3. Read numbers from small RNA sequencing of rapeseed phloem sap.

Supplemental File S1. Arabidopsis miR precursor sequences and primer annealing sites.

Supplemental File S2. Quantitative real-time PCR results for all investigated pri-miR species.

Supplemental File S3. Structures and small RNA reads of P-responsive miRs.

Supplemental File S4. Target gene predictions.

Note Added in Proof

The novel miR described in this work was independently reported by Fahlgren et al. (Fahlgren N, Sullivan CM, Kasschau KD, Chapman EJ, Cumbie JS, Montgomery TA, Gilbert SD, Dasenko M, Backman TW, Givan SA, et al [2009] Computational and analytical framework for small RNA profiling by high-throughput sequencing. RNA 15: 992–1002). To unify the naming, this miR is referred to as miR2111 in the final published version.

	ACKNOWLEDGMENTS

 
We thank Dr. John Lunn (Max-Planck Institute of Molecular Plant Physiology) and Dr. Peter Dörner (University of Edinburgh) for proofreading and suggestions on the manuscript.

Received March 27, 2009; accepted May 18, 2009; published May 22, 2009.

	FOOTNOTES

 
¹ This work was supported by the Max-Planck Society.

² These authors contributed equally to the article.

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Wolf-Rüdiger Scheible (scheible{at}mpimp-golm.mpg.de).

^[C] Some figures in this article are displayed in color online but in black and white in the print edition.

^[W] The online version of this article contains Web-only data.

^[OA] Open Access articles can be viewed online without a subscription.

www.plantphysiol.org/cgi/doi/10.1104/pp.109.139139

^* Corresponding author; e-mail scheible{at}mpimp-golm.mpg.de.

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