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Plant Cell. 2009 Sep; 21(9): 2780–2796.
PMCID: PMC2768930

Genome-Wide Medicago truncatula Small RNA Analysis Revealed Novel MicroRNAs and Isoforms Differentially Regulated in Roots and Nodules[W]


Posttranscriptional regulation of a variety of mRNAs by small 21- to 24-nucleotide RNAs, notably the microRNAs (miRNAs), is emerging as a novel developmental mechanism. In legumes like the model Medicago truncatula, roots are able to develop a de novo meristem through the symbiotic interaction with nitrogen-fixing rhizobia. We used deep sequencing of small RNAs from root apexes and nodules of M. truncatula to identify 100 novel candidate miRNAs encoded by 265 hairpin precursors. New atypical precursor classes producing only specific 21- and 24-nucleotide small RNAs were found. Statistical analysis on sequencing reads abundance revealed specific miRNA isoforms in a same family showing contrasting expression patterns between nodules and root apexes. The differentially expressed conserved and nonconserved miRNAs may target a large variety of mRNAs. In root nodules, which show diverse cell types ranging from a persistent meristem to a fully differentiated central region, we discovered miRNAs spatially enriched in nodule meristematic tissues, vascular bundles, and bacterial infection zones using in situ hybridization. Spatial regulation of miRNAs may determine specialization of regulatory RNA networks in plant differentiation processes, such as root nodule formation.


The spatial configuration of the root system (i.e., the primary roots and the number and length of lateral organs), so-called root architecture, is adapted to the soil environment. The root apex contains meristematic cells that determine root growth and produce all belowground organs. At a certain distance from the root apex, anticlinal and asymmetric divisions of pericycle cells are the initial events of lateral root formation (Malamy, 2005). The complete root system results from the coordinated control of both genetic endogenous programs (regulating growth and organogenesis) and the action of abiotic and biotic environmental stimuli on primary and lateral roots (Jovanovic et al., 2007).

In legumes, such as Medicago truncatula, roots grown under nitrogen starvation conditions are additionally able to interact with specific Rhizobiaceae bacteria to develop a new specialized structure, the nitrogen-fixing root nodule, which is morphologically and functionally different from any other plant organ (Crespi and Frugier, 2008; Oldroyd and Downie, 2008). After a specific molecular exchange of signaling molecules, including bacterial Nod factors, rhizobia infect plant cells and reactivate cell divisions mainly in the inner cortex in front of xylem poles. In M. truncatula, a temperate legume, nodule differentiation is characterized by the presence of a persistent apical meristem (zone I), allowing indeterminate growth and leading in mature nodules to the following zonation: a rhizobial infection region (zone II), followed by a nitrogen-fixing region (zone III), and a senescence region (zone IV) in older organs (Vasse et al., 1990).

A recent revolution in biology is the identification and characterization of regulatory small noncoding RNAs as major regulators of gene expression. In plants, there are two families of small RNAs that repress gene expression at transcriptional or posttranscriptional levels: short interfering RNAs (siRNAs) and microRNAs (miRNAs). These small RNAs play critical roles in a large variety of biological processes, such as development or biotic and abiotic plant responses (Mallory and Vaucheret, 2006; Zhang et al., 2006a; Bartel, 2009; Chuck et al., 2009). In Arabidopsis thaliana, 18- to 22-nucleotide miRNAs are typically encoded in intergenic regions and are generally transcribed by RNA Polymerase II as long transcripts, the primary miRNAs. These primary miRNAs contain an imperfect stem-loop structure from which precursors (pre-miRNAs) are excised through the action of DICER-LIKE1 (DCL1) associated with double-stranded RNA (dsRNA) binding proteins, such as HYL and SER (Lobbes et al., 2006; Dong et al., 2008). The pre-miRNA is further processed by the same DCL1 protein complex to generate a 21-nucleotide duplex miRNA, which is methylated on its 3′ end by HEN1 (Yu et al., 2005). After being exported out of the nucleus by HASTY (Park et al., 2005), the single-stranded miRNA is preferentially incorporated into an RNA-induced silencing complex (RISC) containing the AGO1 protein (Mallory et al., 2008). The imperfect complementary strand to the miRNA in the pre-miRNA is called miR*. The binding of the miRNA (incorporated into the RISC) to mRNA targets leads to degradation and/or translational inhibition of the target.

Large numbers of small RNAs have been recently identified in bryophytes (Axtell et al., 2007), angiosperms (Chen et al., 2006; Barakat et al., 2007; Fahlgren et al., 2007; Pilcher et al., 2007), and unicellular alga (Zhao et al., 2007) by sequencing small RNA libraries. Only a few of them are miRNAs, and recently, consensus rules for miRNA annotation have been proposed (Meyers et al., 2008). In addition, certain miRNAs have been identified using computational tools that are able to predict pre-miRNA hairpin structures (Bonnet et al., 2004; Zhang et al., 2006b). There are at least 20 miRNA families conserved among the four angiosperm species for which highly abundant miRNA populations are available: Arabidopsis, poplar (Populus spp), grapevine (Vitis vinifera), and rice (Oryza sativa). Generally, these miRNAs are encoded by multiple loci and regulate homologous targets in the different species, often mRNAs encoding transcription factors (Bartel, 2004; Jones-Rhoades et al., 2006). In all species analyzed, there are also nonconserved miRNA genes that may correspond to recent evolutionary sequences that recognize transcripts coding for a large diversity of functions (Axtell and Bowman, 2008). Certain proto-miRNAs or young miRNAs are processed by DCL4 (Rajagopalan et al., 2006) and produce additional stem-loop-derived small RNAs due to the sequential activity of DCL4 (Voinnet, 2009).

Arabidopsis siRNAs are found in three classes: (1) repeat-associated siRNAs (rasiRNAs), (2) trans-acting siRNAs (tasiRNAs), and (3) natural antisense transcript-derived siRNAs. Although the sizes of siRNA molecules are very similar to miRNAs, they are generated by distinct pathways (Vaucheret, 2006; Vazquez, 2006). Arabidopsis rasiRNAs are small RNAs of 24 nucleotides that correspond to the most abundant category identified in angiosperm species. They are derived from repetitive genome sequences and are generated by DCL3. The tasiRNAs result from the cleavage of a noncoding TAS transcript by a miRNA and the synthesis of dsRNA molecules through the action of RNA-dependent RNA Polymerase 6. These long dsRNAs are further processed by DCL4 into 21-nucleotide tasiRNAs, which target specific mRNAs in trans (Allen et al., 2005; Gasciolli et al., 2005). Finally, natural antisense transcript-derived siRNAs are produced by DCL1 or DCL2 from overlapping convergent genes forming dsRNAs due to natural antisense transcription (Borsani et al., 2005; Katiyar-Agarwal et al., 2007).

In Arabidopsis, small RNA (sRNA) transcriptomes are now available for several organs and mutants and can be retrieved in databases such as the Arabidopsis Small RNA Project (Gustafson et al., 2005), the Massively Parallel Signature Sequencing small RNA project (Nakano et al., 2006), and miRBase (Griffiths-Jones et al., 2006, 2008). The AthaMap describes 403,173 positions that map with sRNAs in the Arabidopsis genome (Bülow et al., 2009). Recent advances in sequencing technology (Lister et al., 2008) have allowed the discovery of many sRNAs and conserved miRNAs in a large variety of other plants (miRBase; http://microrna.sanger.ac.uk/sequences/), including legumes species, such as soybean (Glycine max; Subramanian et al., 2008) and M. truncatula (Szittya et al., 2008). Several of these conserved miRNAs may play roles in nodulation, a legume-specific process. Indeed, Mtr-miR169 has been shown to posttranscriptionally regulate a Mt HAP2.1 transcription factor induced specifically during symbiosis (Combier et al., 2006), whereas Mtr-miR166 overexpression downregulates expression of at least three HD-ZipIII transcription factors and affects concomitantly root vascular tissue patterning and initiation of symbiotic nodules and lateral roots (Boualem et al., 2008).

In this work, we searched for novel miRNAs from M. truncatula root apexes and nodules using deep sequencing. A total set of 97,028 distinct sRNAs from 20 to 24 nucleotides was obtained that mapped to 182,570 positions in the genome. In addition to a variety of siRNAs and conserved miRNAs, we identified 100 novel candidate miRNAs, encoded by 265 hairpins in the M. truncatula genome. Several miRNAs and specific miRNA isoforms showed distinct expression patterns in nodules and root apexes. In situ hybridization analyses suggested that spatial regulation of miRNA expression may contribute to determine root and nodule growth and differentiation.


Global Analysis of Small RNA Libraries from M. truncatula Nodules and Root Apexes

Our goal was to identify miRNAs from the model legume M. truncatula that could be involved in the regulation of root architecture and/or in nodulation. We therefore constructed three small RNA libraries from mature nodules (21 to 30 d postinoculation with Sinorhizobium meliloti) and from root tips treated or not with 100 mM NaCl during 1 h, a condition that strongly affects root growth (Merchan et al., 2007). Deep 454 pyrosequencing yielded a total of 844,110 reads. After removal of adaptors and tRNA/rRNA-like sequences, 244,366 reads were retained and grouped according to redundancy to identify unique (nonredundant) sequences (Figure 1). Finally, after removal of sequences likely derived from the symbiotic bacteria and size filtering, a total of 97,028 nonredundant sequences, ranging from 20 to 24 nucleotides, was obtained.

Figure 1.
Flowchart for the Identification of M. truncatula miRNAs.

The 21- and 24-nucleotide RNAs were the most abundant sRNA species (Figure 2; see Supplemental Table 1 online), and, as generally described, the 24-nucleotide RNA population was clearly the most diverse. However, in root tips, the set of 21-nucleotide RNAs was around threefold more abundant than in nodules. Interestingly, the expression levels of Mt DCL1 and Mt DCL3 homologs in these tissues, expected to produce essentially 21- and 24-nucleotide RNAs, respectively, correlate with these results (Figure 2, inset). Root apexes, which are enriched in meristematic tissues, may thus contain a larger proportion of miRNAs.

Figure 2.
Distribution of Small RNAs in Nodules and Root Tips.

Mapping of Small RNAs in the M. truncatula Genome

The 21- to 24-nucleotide small RNAs were mapped in M. truncatula nuclear genome version 2.0. In total, 39,203 sRNAs from 21 to 24 nucleotides presented at least one perfect match in the genome (Figure 1). The corresponding 182,570 sRNA-generating loci represented 2% of the sequenced M. truncatula genome. The density of sRNA loci was calculated for each 300-kb region of the genome, and heat maps for each sRNA population were generated. As shown in Figure 3, the 24-nucleotide RNA loci (142,489 in total) are densely distributed all along the genome, even though a bias due to the absence of centromeric regions in the available M. truncatula sequencing effort (Young et al., 2005). By contrast, for the 21- and 22-nucleotide RNAs (27,252 and 26,139 loci, respectively), only 3 and 18 high density regions were detected, respectively. As expected, regions that produced mainly 21-nucleotide RNAs corresponded to intergenic regions. However, surprisingly, some nucleotide binding site–leucine-rich repeat (NBS-LRR) genes also generated exclusively various 21-nucleotide sRNAs (see Supplemental Figure 1 online).

Figure 3.
Global Density Map of the Small RNA Loci in the M. truncatula Genome.

Global expression of potential tasi/miRNAs was analyzed by searching genomic regions carrying 21-nucleotide RNA-generating loci and showing a differential number of reads between nodules and root apexes. Large differences in 21-nucleotide RNA accumulation levels were observed between nodules and root tips (see Supplemental Figure 2 online), including in 6 of the 13 highly expressed regions (in purple). Hence, nodules and root apexes showed drastic differences in their sRNA diversity, suggesting a major change in posttranscriptional regulation of the transcriptome between roots and nodules.

Conserved miRNAs Isoforms Are Differentially Accumulated in M. truncatula Roots and Nodules

To identify conserved miRNAs, we compared the entire set of unique sRNAs to the miRBase v13 database. A total of 2981 M. truncatula sequences showing less than three mismatches with a registered miRNA were identified, corresponding to 12,390 reads (1% of the total reads). These sRNAs belonged to 27 miRNA families previously described in nonlegume species (see Supplemental Table 2 online). In addition, five miRNAs (Gma-miR1507, 1509, 1510, 1511, and 1514) identified in soybean roots inoculated with Bradyrhizobium japonicum (Subramanian et al., 2008) and seven of the Mtr-miRNA candidates found in M. truncatula leaves by Szittya et al. (2008) were retrieved in our libraries.

In most of the conserved miRNA families, different but highly related 21-nucleotide sequences, referred to as miRNA isoforms, were retrieved (see Supplemental Table 2 online). Surprisingly, for many conserved Mtr-miRNAs, isoforms sequenced in our libraries did not correspond to the previously registered Mtr-miRNAs, which thus probably accumulate at low levels in nodules and roots. Interestingly, the accumulation of certain isoforms was statistically different between nodules and root apexes (Figure 4; Fisher's test, P < 0.01). For instance, Mtr-miR164 isoform 2 and Mtr-miR171 isoforms 4 and 5 preferentially accumulated in nodules, whereas the Mtr-miR171 isoform 2 showed an opposite profile. By contrast, Mtr-miR159 isoform 2 and Mtr-miR167 isoform 3 were highly abundant in root tips and undetectable in nodules despite a large number of reads in each sample. These results highlight that differential expression patterns of specific miRNA isoforms exist in diverse tissues.

Figure 4.
Diversity of Conserved miRNA Families in Nodules and Root Apexes.

Size variants of 22 and 24 nucleotide were found for many conserved miRNA families (see Supplemental Tables 3 and 4, respectively, online). The 22-nucleotide variants were generally less abundant than the 21-nucleotide members (between 3.1 and 25%) except for miR167, miR479, and three Mtr-miRNA, 1507, 1509, and 1511. The variants of 23 to 25 nucleotides produced through the action of DCL3 in Arabidopsis (Dunoyer et al., 2004; Vazquez et al., 2008) were generally not identified in our samples. Furthermore, six variants of 24 nucleotides with more than five reads that did not match in the genome showed an AUA extension at their 3′ end. These sRNAs can correspond either to sequencing errors, to nonsequenced regions of the genome, or to miRNAs subjected to postprocessing modifications. Although the addition of AUA has not been reported, miRNA polyuridylation has been observed in hen1 mutants (Li et al., 2005) and occurs at low frequency in wild-type plants (Lu et al., 2006).

Identification of Precursors from 100 New miRNAs in M. truncatula

One of the important features that distinguishes miRNAs from siRNAs is the precise excision of miR:miR* duplexes from hairpin structures (Meyers et al., 2008). The 800-bp genomic regions surrounding each 20- to 22-nucleotide unique sequence (herein referred to as defining sRNA) were thus analyzed for their ability to fold into stem-loop structures using the MIRFOLD program (Billoud et al., 2005). Stable secondary structures and conserved criteria of the predicted miR:miR* duplex (Jones-Rhoades and Bartel, 2004) were found in 4663 hairpins that were classified in five categories depending on their sRNA profiling along the stem-loop.

The complete list of hairpins is available at our website (http://medicago.toulouse.inra.fr/MIRMED) with sRNA profiles, defining sRNA, sequence, and read numbers in nodule or root tip libraries. A BLASTN searching system to check for query sRNAs is available. The sRNAs sequences can be found in the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) using the series accession GSE15438 and sample accessions GSM387472, GSM387473, and GSM387474. The entire set of sRNA sequences is available for downloading from the project website.

Comparison of the defining sRNAs against miRBase revealed that 73 hairpins corresponded to 24 registered plant miRNA families (Figure 1; see Supplemental Table 2 online), including 40 that showed both miRNA and miR* reads (class 1). For 31 others, only the miRNA was found (class 3a). The conserved families contained between one and thirteen Mtr-miRNA genes with highest numbers for Mtr-miR166, Mtr-miR395, and Mtr-miR399. All Mtr-miR395 hairpins were organized into a large cluster on chromosome 5, whereas four different clusters were reported in Arabidopsis and rice (Guddeti et al., 2005). Out of the four Mtr-miR399 isoforms identified, genes for isoforms 1 and 3 were grouped in a same cluster on the chromosome 6, while hairpins encoding the isoform 4 were clustered on chromosome 4. In Arabidopsis and rice, miR399 genes are also partially clustered (miRBase). Finally, for Mtr-miR166, two tandem clusters were identified, at least one corresponding to a polycistronic precursor present in The Institute for Genomic Research (TIGR) EST database (TC135405; Boualem et al., 2008).

To select new miRNA candidates, we removed the defining sRNAs having >50 matches in the genome, as they may be repeat-associated siRNAs rather than miRNAs. These diverse filters yielded a total of 265 hairpins (73 of class 1 and 192 of class 3a), corresponding to 100 different novel Mtr-sRNAs (Table 1; see Supplemental Table 3 online for precursor details). These miRNA candidates and their precursors have been accepted by miRBase and annotated Mtr-MIR2111, Mtr-MIR2119, and from Mtr-MIR2585 to 2680, respectively. Half of them began with a U at their 5′ end, a conserved character of miRNAs incorporated in the AGO1-containing RISC complex (Mi et al., 2008). Annotation of their genomic loci incited us to further exclude six candidates mapping to exons of protein coding genes. Interestingly, among the 94 remaining Mtr-miRNAs, five were only located in annotated introns, adding to the restricted list of intronic miRNAs in plants (Brown et al., 2008). Moreover, Mtr-MIR2597, 2614, 2639, 2642, and 2645 were exclusively encoded by hairpins in antisense position to exons of protein coding genes (see Supplemental Table 5 online). Finally, mapping on six other plant genomes revealed that 23 of the new Mtr-miRNA candidates were specific from legume species or from M. truncatula (Table 1).

Table 1.
New miRNAs from M. truncatula

Mtr-miRNA candidates were grouped into 98 families, from which 30 contained at least one precursor where both miR and miR* were sequenced (class 1). Among them, most displayed all characteristics of canonical pre-miRNAs (Meyers et al., 2008) and thus corresponded to genuine miRNAs (examples in Supplemental Figure 3A online). Curiously, 10 precursors of class 1 produced 23/24-nucleotide RNAs from the predicted miR* region instead of a typical 21-nucleotide miR* (see Supplemental Figure 3B online). Finally, 68 families were composed of structured stem-loop precursors producing a unique sRNA with at least two reads (class 3a) and presenting all criteria of bona fide pre-miRNAs (see Supplemental Figure 3A online). However, as the miR* could not be detected, likely due to low expression levels, they can only be considered as miRNA candidates. The new Mtr-miRNAs were encoded by 1 to 25 genes with diverse distributions in the genome. For instance, the 25 genes coding for Mtr-MIR2630 were interspersed on the eight chromosomes, whereas the 19 precursors of Mtr-MIR2111 were grouped in a 100-kb region of chromosome 7 (see Supplemental Table 5 online). Although no corresponding transcript was identified in EST databases, the overlapping or close proximity of certain hairpins suggest that cotranscription is possible.

Target Predictions for Conserved and New Mtr-miRNAs

Generally, targets of plant miRNAs have perfect or near-perfect complementary sites, allowing their identification using bioinformatical prediction methods (Rhoades et al., 2002). We used the miRanda 1.9 program (Enright et al., 2003) to search for antisense hits of the conserved and new miRNAs within the M. truncatula gene index (MtGI Release 9.0). The miRanda raw results were postprocessed to consider the rules established for plant targets (Jones-Rhoades and Bartel, 2004). For the known miRNAs, 67 targets were predicted (see Supplemental Table 6 online). Transcripts homologous to targets already validated in Arabidopsis were identified for 14 miRNA families, sometimes in BAC genomic databases. In Arabidopsis, miR390, a key element of the tasiRNA pathway, targets TAS3 transcripts (Vaucheret, 2006). A TAS3 homolog that contained one predicted miR390 binding site was found in BAC AC186679, and TAS3-derived siRNAs were present in our libraries (E4D3Z3Y01EPP0U and E8W526M04JHWF1) and detected by RNA gel blots (Figure 5). Hence, the tasiRNA biogenesis pathway seems conserved in M. truncatula. Additionally, 48 new transcripts contained complementary sites for conserved miRNAs and were classified according to their Arabidopsis best hit (see Supplemental Table 6 online).

Figure 5.
Organ-Specific Expression of M. truncatula mi/siRNAs.

For the 100 novel Mtr-miRNA candidates, 480 targets were predicted (see Supplemental Table 7 online). The number of targets per miRNA varied between 0 (39 families) and 122 (Mtr-MIR2695). According to their INTERPRO annotation (Hunter et al., 2009), 60% were either unknown or encoding hypothetical proteins. We grouped the remaining transcripts into nine main functional categories (see Supplemental Table 7 online). Few targets corresponded to transposons, suggesting that the corresponding small RNAs (Mtr-MIR2594, 2628, and 2647) may likely be rasiRNAs rather than miRNAs. Several putative targets of novel miRNAs were transcription factors (TFs), such as a subunit of the transcription initiation factor IIF, two zinc-finger proteins, a TF containing a SANT domain, two members of the WRKY family, two helix-loop-helix DNA binding proteins, and a homeodomain protein (Udvardi et al., 2007). In addition, a No Apical Meristem TF was predicted to be regulated by Mtr-MIR2593. Targets involved in protein folding/degradation corresponded to eight chaperonins, 10 protease inhibitors, and 16 F-box proteins potentially regulated by four different miRNAs (Mtr-MIR2585, 2619, 2643, and 2664). Finally, 14 predicted targets were NBS-LRR disease resistance genes, potentially regulated by nine Mtr-miRNA candidates, suggesting a complex and specific regulation of defense processes by miRNAs. In Brassica napus, a miRNA was also recently predicted to target a virus-induced NBS-LRR gene (He et al., 2008). Finally, we found three putative targets annotated as late nodulins. Two of them (TC124639 and AW980539) presented binding sites for different small RNAs (Mtr-MIR2590 and 2598). Interestingly, these transcripts encoded putative members of the large family of nodule-specific Cys-rich peptides (Mergaert et al., 2003).

Several Conserved and New miRNAs Show Differential Accumulation in M. truncatula Roots and Nodules and in Response to Salinity

The expression pattern of some Mtr-miRNAs was analyzed using RNA gel blots (Figure 5) in root tips treated or not with 100 mM NaCl, mature nodules, and seedlings. In all cases, we observed a unique signal corresponding to a mature sRNA (21 or 22 nucleotides). Five of the 13 conserved miRNAs analyzed (miR159, miR162, miR166, miR390, and miR399) presented similar expression levels in root apexes and nodules. By contrast, miR160, miR167, miR172, and miR398 were more abundant in nodules, whereas miR169, miR171, miR393, and miR396 levels were higher in root tips. Except miR159, miR167, miR171, and miR390, the tested miRNAs were more abundant in belowground organs than in whole seedlings. Salt stress decreased levels of several known miRNAs, such as miR390, miR396, and miR399 in root tips, whereas miR172 seemed the only conserved miRNA slightly induced by this environmental constraint.

Despite their low read number, most of the new or Mt-specific miRNAs gave detectable expression levels in RNA gel blot analyses (Figure 5). This was also the case for Mtr-sRNA107, which did not match to the sequenced genome but to a nodule EST with a pre-miRNA-like secondary structure (AW684497). In contrast with Mtr-MIR2088, 2111, 2586, 2590, 2607, and 2612, Mtr-miRNA1509, 1510, and 2609 accumulated differentially in root tips and nodules. Moreover, Mtr-MIR2612 seemed to be salt responsive. We also analyzed the accumulation of siRNAs identified in our libraries: one tas3-derived siRNA and a putative repeat-associated siRNA Mtr-sRNA200 found in 64 loci. Interestingly, this sRNA seemed to accumulate specifically in nodules. Hence, variable expression patterns of mi/siRNAs were identified in root and nodules or in roots submitted to an abiotic stress.

Several miRNAs Are Associated with Nodule Meristems

To study their tissue-specific expression, we thus performed in situ hybridization experiments on mature nodules (21 to 30 d postinoculation) for nine Mtr-miRNAs. Except for miR396 that was undetectable, all Mtr-miRNAs, including new ones (Mtr-MIR2586 and Mtr-sRNA107), accumulated at least in the meristematic zone (Figure 6). In addition, miR167 (targeting auxin response factors) was also localized in the differentiating peripheral vascular bundles (Figures 6E and 6F). MiR398, a miRNA involved in detoxification of reactive oxygen species (Sunkar et al., 2006), and miR172 targeting APETALA2-related TFs in Arabidopsis (Aukerman and Sakai, 2003) showed broader expression patterns in the differentiating zone than other miRNAs, as shown on consecutive nodule sections (Figures 6C, 6D, 6I, and 6J). Finally, one new isoform of miR399 (isoform 6 in Supplemental Table 2 online) was the only candidate that could be detected in the nitrogen-fixing zone (Figures 6G and 6H).

Figure 6.
Tissue-Specific Expression of mi/siRNAs in Mature Nodules.

Spatial localization of miRNA expression showed a majority of miRNAs expressed in the meristematic zone. Therefore, miRNA-mediated regulation may be linked to nodule development rather than functioning.


The aim of this work was to identify new miRNAs at a genome-wide level linked to the regulation of root architecture and nodule formation in M. truncatula. We identified 100 new miRNA candidates. We showed that specific isoforms had contrasting expression patterns between root tips and nodules. Global and spatial analyses suggest an enrichment of miRNAs in the meristematic zones of root and nodules.

In the model legume M. truncatula, 38 miRNA genes belonging to 17 families are registered in miRBase v13, including four specific miRNAs identified by deep sequencing in leaves (Mtr-miR2086 to 2089; Szittya et al., 2008). We expanded this set by identifying 59 new precursors of known miRNAs as well as 265 precursors for 100 new miRNA candidates. According to the recent criteria for plant miRNAs (Meyers et al., 2008), at least 30 of these new miRNA genes should actually be considered as genuine miRNA precursors, based on the detection of both the miRNA and the miR* in our libraries. The novel miRNA candidates, mainly present as single genes or in few copies, were low to moderately abundant and often presented a large variety of predicted targets, as shown in Arabidopsis (Voinnet, 2009). For these other miRNA candidates, deeper sequencing approaches may hopefully permit detection of the miR*. In addition to novel families displaying criteria of genuine plant miRNAs (Meyers et al., 2008), we identified 11 families of atypical precursors encoding a 21- to 22-nucleotide miRNA candidate and a 24-nucleotide RNA on the opposite strand of the hairpin. They are therefore likely to be processed both by DCL1 and DCL3. However, this situation differs from that reported in Arabidopsis, where miRNAs of 24 nucleotides were sometimes observed on RNA gel blots (Dunoyer et al., 2004; Vazquez et al., 2008). Very few 24-nucleotide miRNA variants, coming from the same strand as the 21-nucleotide miRNA, were detected in our libraries, suggesting that accumulation of long miRNAs does not generally occur in roots and nodules of M. truncatula.

The advanced knowledge of the M. truncatula genome allowed us to analyze the genomic organization of Mtr-miRNA genes. As expected, the great majority was mapped in regions annotated as intergenic or non-protein-coding genes. Nevertheless, an Mtr-miR399 and six new miRNA precursors were complementary to protein coding genes and could be related to the recently described nat-miRNA class (Lu et al., 2008). In addition, precursors of seven miRNAs (miR395, miR398, and five novel candidates) matched to introns. In animals, intronic miRNAs are frequent (Brown et al., 2008) but, to our knowledge, only one Arabidopsis miRNA, Ath-miR838, derives from the intron of a protein-coding gene, DCL1, but does not target other mRNA (Brodersehn et al., 2008). Likely, this particular processing is a regulatory mechanism that allows DCL1 levels to be controlled (Rajagopalan et al., 2006). During evolution, the genomic organization of conserved miRNA gene families have been considerably modified (Axtell and Bowman, 2008; Zhang et al., 2009). For instance, the rice miR395 gene family is organized into four clusters of 24 genes, and three of them are segmental duplications (Guddeti et al., 2005). By contrast, all Mtr-miR395 precursors matched to a unique region. We also found three miRNA families (Mtr-miR166, Mtr-miR399, and Mtr-MIR2601) organized in clusters, as described for many miRNAs in rice (Cui et al., 2009).

To date, the set of legume-specific miRNAs is relatively small. In soybean, Subramanian et al. (2008) found 20 conserved miRNAs and 35 novel candidates in roots infected with the symbiotic bacteria B. japonicum. For three of them, a miR* was sequenced and three additional novel miRNA candidates could be detected by RNA gel blots. Although we analyzed closely related tissues, we only found five of the novel soybean miRNAs. In this study, out of the 100 new candidates, eight were legume specific (at least one hit with less than three mismatches found in G. max and/or Lotus japonicum), and 15 were only found in M. truncatula. By contrast, when only one substitution was allowed, as proposed by Rajagopalan et al. (2006) for Arabidopsis-specific miRNAs, only 10 novel Mtr-sRNAs from our data set were found in nonlegume species.

To our knowledge, the only small RNA libraries generated from underground tissues were from soybean roots infected with B. japonicum (Subramanian et al., 2008) or mature nodules (Wang et al., 2009). Both M. truncatula roots and nodules have an indeterminate growth and contain a gradient of differentiation between an active persistent meristem and fully differentiated cells (Patriarca et al., 2004; Oldroyd and Downie, 2008). As for long mRNA transcriptomes (Benedito et al., 2008), we discovered extensive differences between their small RNA populations. In the several plants studied, the 24-nucleotide sRNA class is usually highly diverse and encompasses heterochromatic and repeat-associated siRNAs, as also observed in M. truncatula even though centromeric regions were avoided (Young et al., 2005). In addition, an enrichment of 21-nucleotide reads was found in root tips correlated with a lower expression of DCL3. In Arabidopsis, a similar distribution bias could also be observed in shoot apical meristems, associated to a lower DCL3 expression compared with leaves (Vazquez et al., 2008).

Many conserved but also new Mtr-miRNAs, such as Mtr-MIR2586 and Mtr-sRNA107, which both target TFs, showed differential expression between roots and nodules and accumulated in the nodule meristematic zone. This reinforces the hypothesis that plant miRNAs could preferentially accumulate in undifferentiated cells, like in animals (Zhang et al., 2006c), and that they could be essential players of stem cell self-renewal (Chuck et al., 2009). An additional specific localization was observed in the infection zone for miR172 and miR398, suggesting roles for these miRNAs in cell differentiation or infection by the symbiotic bacteria. Moreover, miR167 strongly accumulated in the nodule peripheral vascular tissues. This miRNA was previously detected in vascular tissues in Nicotiana benthamiana but not in Arabidopsis (Válóczi et al., 2006); thus, its expression could be differentially regulated across species and organs.

Statistical analysis of read numbers also revealed differential accumulation of certain miRNA isoforms between root tips and nodules. As recently proposed for miR169 and its NFY-A TF targets in the context of the response to drought and abscisic acid signaling (Li et al., 2008), different isoforms of a miRNA may regulate distinct sets of targets (Schwab et al., 2005) and define complex specificities of miRNA action at spatio-temporal level. Here, for instance, we found that the most abundant miR159/319 isoforms in our libraries were predicted to target transcripts encoding unknown proteins instead of the TCP TF described in Arabidopsis (Palatnik et al., 2007). The output of miRNA action may depend on the availability of specific AGO paralogs but also of specific miRNA isoforms and distinctive mRNA targets within a given cell type (Brodersen and Voinnet, 2009) coupled with spatially restricted expression patterns. Likely, the action of miRNAs controlling mRNA stability and translation integrates into a much broader framework of possible regulatory mechanisms (Voinnet, 2009).

Few Mtr-miRNAs have been shown to play roles in symbiosis or root development (Combier et al., 2006; Boualem et al., 2008). Although the predicted targets identified here require validation, interesting new candidates emerged. Mtr-miR396, preferentially accumulating in root tips, appeared to target growth regulating factors (as in Arabidopsis) but also a TF with a DNA binding domain B3 homologous to the Arabidopsis transcription repressor Related to Vernalization1. Furthermore, the main isoform of Mtr-miR398 was predicted to target a putative histone deacetylase in addition to the conserved copper superoxide dismutase CSD1 target (Abdel-Ghany and Pilon, 2008). Finally, Mtr-miR160 and Mtr-miR167 accumulated in nodule meristems and target auxin response factors, suggesting a complex regulation of auxin responses in the indeterminate nodules (Mathesius, 2008; Oldroyd and Downie, 2008). In Arabidopsis, Ath-miR393 and Ath-miR394 (Jones-Rhoades and Bartel, 2004) also target TIR1 and other F-box proteins linked to auxin action, and the pathogen-mediated induction of Ath-miR393 could inhibit defense responses, a process also occurring during symbiosis (Gray et al., 2001; Navarro et al., 2006; Oldroyd and Downie, 2008).

Altogether, the large diversity of conserved and novel miRNAs identified offers new perspectives for the comprehension of the complex spatio-temporal regulation of the transcriptome during nodule organogenesis and root development.


Plant Material

Seeds of Medicago truncatula Jemalong A17 were surface-sterilized for 20 min in bleach, washed several times with sterile water, and transferred to 1.5% agar plates at 4°C for 1 week in the dark. Seedlings were grown in perlite:sand (3:1) pots under 16 h light at 24°C and watered with a nutritive solution of low nitrogen content (solution“i”; Blondon, 1964). One-week-old plants were inoculated with Sinorhizobium meliloti 2011 strain (DO600 = 0.05). Mature nodules were harvested 21 to 30 d postinoculation and immediately frozen in liquid nitrogen or embedded in paraplast. Root tips (1 to 2 cm) were obtained from plants 10 to 12 d after germination grown in perlite:sand pots disposed on a metal grid, with root tips growing in a rich SN/2 nutritive solution. For salt treatment, root tips were treated by immersion for 1 h in the same nutritive solution supplemented or not with 100 mM NaCl as described by Gruber et al. (2009).

Construction and Cloning of Small RNA Libraries

Small RNA libraries were constructed as described by Lagos-Quintana et al. (2002): 500 μg of total RNA, extracted with the TRIZol reagent (prepared by us with the same components and concentrations as the commercial Invitrogen reagent) were ligated to the following custom RNA adaptors (Dharmacon): A3 (pAUUGAUGGUGCCUACA-IdT with p, phosphate, and idT, inverted deoxythymidine) and then A5-A or A5-B (A5-A, AUCGUAGGCACCUGAUA, or A5-B, AUCGUAGCCACCUGAUA) for nodule and root apexes samples, respectively. After reverse transcription, cDNAs were amplified 20 cycles with primers corresponding to the adaptors (PCR-A3, 5′-CAGAGTGTAGGCACCATCAAT-3′, and PCR-A5A, 5′-GCACATCGTAGGCACCTGATA-3′, or PCR-A5-B, 5′-GCACATCGTAGCCACCTGATA-3′). The 60- to 70-bp cDNA fraction, purified from 10% nondenaturing PAGE, was then sequenced by 454 pyrosequencing (Margulies et al., 2005) at the Genoscope (Commissariat à l'Energie Atomique, Evry, France).

Small RNA Sequence Identification

Sequence adaptors were identified using crossmatch-minmatch 8-minscore 10 (http://www.incogen.com/public_documents/vibe/details/crossmatch.html). Reads with one of the three following adaptor-sRNA patterns (A3-sRNA-A5; A3-sRNA and sRNA-A5) were reverse complemented. Adaptor sequences were then removed and reads of 15 to 30 nucleotides were selected and compared with a database of ribosomal and tRNAs. The ribosomal sequences were obtained by combining a GenBank extraction of Fabaceae and S. meliloti with the M. truncatula ribosomal sequences. The tRNA database was built by merging Rfam tRNA sequences (Gardner et al., 2009), S. meliloti annotated tRNAs, and the tRNAScan-SE (Lowe and Eddy, 1997) predictions obtained on the M. truncatula genome release 2. The search of ribosomal and transfer RNAs was performed using NCBI-BLASTN with a Wordsize of 4 (-W 4; Altschul et al., 1997), and reads showing two or less mismatches were discarded from further analyses. Mapping of the small RNA set against the S. meliloti genome was performed with NCBI-BLASTN (-W 4), and sequences with 0 or 1 mismatch were removed. The remaining reads were computed for sequence redundancy (wu-nrdb).

Genome Mapping and Comparative Genomics

The set of unique sRNA sequences was mapped in the M. truncatula genome release 2 using NCBI-BLASTN with a Wordsize of 4 (-W 4; Altschul et al., 1997). The number of loci was computed by clustering overlapping reads, considering that one locus is a region of 25 bp that produced at least one sRNA from 20 to 24 nucleotides. Mapping of defining sRNAs against other plant genomes (links are provided in the project website) was performed with NCBI-BLASTN (-W 4). A postprocess filter was applied to remove hits mapping with mismatches on M. truncatula genome or with more than three mismatches for other genomes.

To visualize the global distribution of sRNAs along the genome (Figure 3; generated by CIRCOS, http://mkweb.bcgsc.ca/circos/), the eight chromosomes (plus chromosome 0; i.e., sequenced BACs not yet attributed to any chromosome) were divided into 942 nonoverlapping regions of 300 kb, and the number of sRNA loci per region was calculated. The density of sRNA loci was then visualized based on a color gradient (from white to purple). For 21- to 22-nucleotide RNAs, the density increment was based on 20 loci/region, whereas for the 24-nucleotide RNAs, which are much more diverse, the increment was based on 60 loci/region. The maximal density thus corresponded to at least 100 loci/region for the 21- and 22-nucleotide RNAs and 300 loci/region for the 24 nucleotide RNAs. For expression levels, the abundance of 21 nucleotide reads matching to each 300-kb genomic region was calculated and expressed as a percentage of the total number of 21-nucleotide reads in nodule and root tips, respectively. A color scale was used for visualization from white (<0.1%) to purple (>1%).

Analysis of Isoform Composition of the miRNA Families

Nonredundant sequences from 20 to 24 nucleotides were annotated using NCBI-BLASTN (-W 4) to scan miRBase v12 (up to three mismatches; Griffiths-Jones et al., 2006). In each miRNA family, the different 21-nucleotide sequences were called isoforms and classified by decreasing read number, with isoform 1 being the most abundant. To compare the global composition of each miRNA family between nodules and root tips, an Exact χ2 test was performed with XLSTAT using the Montecarlo sampling method (P < 0.01). The specific accumulation of individual isoforms in one library compared with the other was then tested using a Fisher's exact probability test (P < 0.01).

miRNA Precursor Detection and Folding

The nonredundant small RNA sequence database was mapped using NCBI-BLASTN on the M. truncatula genome v2 (http://medicago.org/genome). For reads ranging from 20 to 22 nucleotides, a search of potential precursor structures was performed by extracting the genomic context (400 bp upstream and downstream) surrounding the position of the sRNA sequence called defining sRNA and by analyzing those regions with MIRFOLD (Billoud et al., 2005). Multiple structural predictions were accepted when their folding energy was not more different than 10 kcal/mol of the best candidate. Only the putative pre-miRNA precursors with a folding energy lower than –30 kcal/mol were selected. The folding of precursors identified on EST databases was performed using RNAFold software (Hofacker, 2004).

miRNA Precursor Annotation

Sequences of 20, 21, and 22 nucleotides were sorted out in all libraries and considered as defining RNA for a particular precursor using a greedy algorithm that scans the list of small RNAs from the highest to the lowest number of reads. For each defining RNA, the previously detected precursors were then annotated with all sequences ranging from 20 to 24 nucleotides from the libraries. Finally, the defining sRNAs used to annotate the precursor were removed from the list of candidates. The process stopped when all 20- to 22-nucleotide small RNAs have been assigned to a precursor.

miRNA Precursor Classification

Annotated precursors showing a free folding energy higher than −30 kcal/mol, with a predicted miR:miR* duplex (the defining RNA being the miR) presenting more than three consecutive mismatches, more than two gaps, or in total more than seven mismatches/gaps were discarded (Jones-Rhoades et al., 2006; Meyers et al., 2008). Remaining precursors were classified in five classes depending on the coverage of the hairpin with 20- to 24-nucleotide RNAs. Precursors of class 1 only produced small RNAs corresponding to the predicted miR and miR* (i.e., small RNAs in a 25-bp region around the miR:miR* predicted region to consider two nucleotide overhangs linked to DCL action); class 2 hairpins contain both predicted miR and miR* and additional sRNAs, with lower abundance, outside this region; class 3 involved precursors with reads on the defining sRNA region only (3a, at least two reads; 3b, only one read); class 4 were precursors containing the defining sRNA plus reads of lower abundance outside the predicted miR:miR* duplex. Finally, class 5 were hairpins that generate sRNAs of higher abundance than the defining RNA outside of the predicted miR:miR* region. To identify the precursors of conserved miRNAs, defining miRNAs were compared with miRBAse v13 using NCBI-BLASTN (-W 4) with a tolerance of three mismatches.

miRNA Target Prediction

The prediction of miRNA targets was performed using the Miranda 1.9 software (John et al., 2004), modified to consider criteria available for plant miRNA targets and the MtGI9 as target database (Lee et al., 2005). Only alignments of 21 bp were considered and filtered on the basis of their pairing: (1) positions 10 and 11 must be paired and (2) alignment score must be lower than 3 (gap cost = 2; mismatch cost = 1; GU pair cost = 0.5; Jones-Rhoades and Bartel, 2004). As many EST/TCs are incorrectly annotated in TIGR databases, putative targeted transcripts were reannotated by combining domain content detection using InterproScan (Hunter et al., 2009) and a NCBI-BLASTX against the Arabidopsis thaliana proteins TAIR database release 8 (Poole 2007). Hits spanning <50% of the length of the Arabidopsis protein or with e-values higher than 10−3 were removed.

MIRMED Database

A chado database (http://www.gmod.org) was set up to handle genomic data as the IMGAG gene models v2, tRNA-ScanSE prediction, EST mapping (June, 2008) both by Genomethreader (Gremme et al., 2005), and by PASA (Haas et al., 2003). In addition, the database was loaded using sRNA reads mapped on the M. truncatula genome and annotated precursors. The project database relies on gbrowse/chado for visualization at the genome scale and on an extension of the LeARN annotation platform (Noirot et al., 2008) for querying and for the visualization of secondary structures and precursor annotations. For each precursor, the genomic position and a representation plot of the stem-loop depicting either the 21-nucleotide RNAs (including the defining RNA) or all sRNAs (from 20 to 24 nucleotides) can be retrieved. LeARN and gbrowse user interfaces are cross-linked to permit an efficient browsing. In addition, Mtr-miRNAs have been deposited in miRBase. The website address is http://medicago.toulouse.inra.fr/MIRMED.

RNA Gel Blot Analysis

Total RNA from roots tips (10 to 12 d after germination), mature nodules (21 to 30 d after S. meliloti inoculation), and 4-d-old in vitro–grown seedlings were extracted with TRIZol reagent (Invitrogen). For RNA gel blots, 10 μg of RNA were separated in 15% polyacrylamide-7 M urea gel and transferred to a Hybond NX membrane (Amersham) as described by Hirsch et al. (2006). RNAs were fixed with 200 mM N-Ethyl-N′-3-dimethylaminopropyl carbodiimide hydrochloride (Sigma-Aldrich) following Pall et al. (2007). Blots were hybridized with [γ-32P]ATP end-labeled oligonucleotides (using a T4 Polynucleotide kinase; Fermentas). An oligonucleotide probe complementary to U6 snRNA was used to normalize RNA concentrations.

RT-PCR Experiments

M. truncatula genes encoding AtDCL1 and AtDCL3 homologs (90 and 60% of similarity, respectively) were found in BACs AC150443 and AC137830, respectively. Specific primers MtDCL1i-Fwd, 5′-CAACACAAAATGGACATAGACAACC-3′, MtDCL1i-Rev, 5′- CAAGCATTTTCTTATTTTGGAGATG-3′, MtDCL3i-Fwd, 5′-AGTGTTCGAGCATTATGTGGTTC-3′, and MtDCL3i-Rev, 5′-TGAAATGACAGAAGTCTTCACCA-3′, were used for RT-PCR experiments to compare gene expression in nodules and root tips (as described in Hirsch et al., 2006). Specific primers of the Mt RBP1 gene were used as constitutive controls in nodules and roots (5′-AGGGGCAAGTTCCTTCATTT-3′; 5′-GGTAGAAGTGCTGGCTCAGG-3′) as described by Boualem et al. (2008).

In Situ Hybridization

M. truncatula mature nodules, 21 to 30 d postinoculation were processed for in situ hybridization as described by Boualem et al. (2008). Modified LNA oligonucleotides (Exiqon) complementary to mi/siRNAs were end-labeled with the DIG Oligonucleotide 3′-End Labeling kit (Roche Applied Science) and used as probes. Antisense probes to the Arabidopsis-specific miR773 (Lu et al., 2006) and the carbonic anhydrase Mt Ca1 (Coba de la Peña et al., 1997) were used as negative and positive controls, respectively.

miRBase Annotation of the New Mtr-miRNAs

After submission to miRBase (number 4a71beab), the 98 newly identified Mtr-miRNA families were named Mtr-MIR2111, Mtr-MIR2119, and from Mtr-MIR2585 to 2680.

Supplemental Data

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

  • Supplemental Figure 1. Genome Browser View of a 21-Nucleotide sRNA Dense Region.
  • Supplemental Figure 2. Global Expression of the 21-Nucleotide sRNA Loci in Nodules and Root Tips.
  • Supplemental Figure 3. Predicted Fold-Back Structures of Selected Novel miRNA Genes from M. truncatula.
  • Supplemental Figure 4. Functional Categories of the Novel Predicted miRNA Targets.
  • Supplemental Table 1. Global Analysis of the Nodule and Root Apex Small RNA Libraries.
  • Supplemental Table 2. Known Mtr-miRNAs and Their Precursors.
  • Supplemental Table 3. The 22-Nucleotide Variants of the Conserved miRNAs.
  • Supplemental Table 4. The 24-Nucleotide Variants of the Conserved miRNAs.
  • Supplemental Table 5. Precursors of the Novel Mtr-miRNAs.
  • Supplemental Table 6. Predicted Targets for the Known miRNAs.
  • Supplemental Table 7. Predicted Targets for the New Mtr-miRNA Candidates.

Supplementary Material

[Supplemental Data]
[Supplemental Data]


We thank Hervé Vaucheret (Laboratory of Cell Biology, Institut National de la Recherche Agronomique, Versailles, France) for discussions and comments on the manuscript, Olivier Voinnet and Ana de Luis (Institute of Plant Molecular Biology, Centre National de la Recherche Scientifique, Strasbourg, France) for helpful advice, the “Medicago Genome Sequencing Consortium” for access to the Medicago genome sequence Mt2.0, the facilities of the Imagif Cell Biology Unit of the Gif campus (www.imagif.cnrs.fr), which is supported by the “Conseil Général de l'Essonne” for microscopy, and Genoscope (Commissariat à l'Energie Atomique, Evry, France) for 454 sequencing. L.N. was the recipient of a fellowship from the European program Diputacion General de Aragon-Caja Inmaculada, Spain. This work was supported by the FP6 EEC-GLIP and the ANR-DIAGNOGENE projects.


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.plantcell.org) is: Martin Crespi (rf.fig-srnc.vsi@ipserc).

[W]Online version contains Web-only data.



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