- Research article
- Open Access
Genome-wide identification of microRNA and siRNA responsive to endophytic beneficial diazotrophic bacteria in maize
- Flávia Thiebaut†1,
- Cristian A Rojas†2,
- Clícia Grativol1,
- Mariana Romeiro Motta1,
- Tauan Vieira1,
- Michael Regulski3,
- Robert A Martienssen3,
- Laurent Farinelli4,
- Adriana S Hemerly1 and
- Paulo CG Ferreira1Email author
© Thiebaut et al.; licensee BioMed Central Ltd. 2014
- Received: 8 January 2014
- Accepted: 22 August 2014
- Published: 6 September 2014
Small RNA (sRNA) has been described as a regulator of gene expression. In order to understand the role of maize sRNA (Zea mays – hybrid UENF 506-8) during association with endophytic nitrogen-fixing bacteria, we analyzed the sRNA regulated by its association with two diazotrophic bacteria, Herbaspirillum seropedicae and Azospirillum brasilense.
Deep sequencing analysis was done with RNA extracted from plants inoculated with H. seropedicae, allowing the identification of miRNA and siRNA. A total of 25 conserved miRNA families and 15 novel miRNAs were identified. A dynamic regulation in response to inoculation was also observed. A hypothetical model involving copper-miRNA is proposed, emphasizing the fact that the up-regulation of miR397, miR398, miR408 and miR528, which is followed by inhibition of their targets, can facilitate association with diazotrophic bacteria. Similar expression patterns were observed in samples inoculated with A. brasilense. Moreover, novel miRNA and siRNA were classified in the Transposable Elements (TE) database, and an enrichment of siRNA aligned with TE was observed in the inoculated samples. In addition, an increase in 24-nt siRNA mapping to genes was observed, which was correlated with an increase in methylation of the coding regions and a subsequent reduction in transcription.
Our results show that maize has RNA-based silencing mechanisms that can trigger specific responses when plants interact with beneficial endophytic diazotrophic bacteria. Our findings suggest important roles for sRNA regulation in maize, and probably in other plants, during association with diazotrophic bacteria, emphasizing the up-regulation of Cu-miRNA.
- Herbaspirillum seropedicae
- Azospirillum brasilense
Plants have a complex mechanism of gene expression regulation that influences their development, adaptation and response to biotic and abiotic interactions. One of these mechanisms involves sRNA and can act by silencing genes at a transcriptional or post-transcription level [1, 2]. In plants, sRNA is 20 to 24 nucleotides (nt) in length, and can be divided into two categories: microRNA (miRNA) and small interfering RNA (siRNA), both produced by RNase III-like enzymes called DCLs, or DICER-like enzymes [3, 4]. The type of precursor molecules and the enzymes involved in their biogenesis and function can differentiate these sRNA classes .
MiRNA is a class of sRNA derived from single-stranded precursors with self-complementary regions, forming a hairpin structure that is processed by DCL, particularly DCL1, together with a dsRNA-binding protein, HYPONASTIC LEAVES 1 - HYL1 . After cleavage, a miRNA/miRNA* duplex is produced and one strand is incorporated into an RNA-induced silencing complex (RISC), where the miRNA associates with an Argonaute protein, most frequently the AGO1, guiding the control of target expression . MiRNA can regulate their target by cleavage of messenger RNA, translational repression or transcriptional inhibition [8–10]. MiRNA is the best-characterized class of plant sRNA and they are highly conserved among related plant species . Despite conservation of miRNA, a recent study has shown that new miRNA can be gained and old ones can be lost, with a rate of birth and death of the Arabidopsis miRNA genes around one per 1.2-3.3 million years . Accordingly, the miRNA class can be divided into conserved families and species-specific miRNA. In contrast, siRNA is processed from longer double-strand RNA and can be divided into natural antisense transcript siRNA (nat-siRNA), secondary siRNA, like ta-siRNA whose precursor depends on cleavage of miRNA targets, and heterochromatic siRNA (hc-siRNA) produced from intergenic or repetitive regions . At least three RNA-dependent RNA polymerases (RDR1, RDR2 and RDR6) are needed to form siRNA precursors [13–15]. Like miRNA, the precursor of siRNA is processed by DCL and loaded into a RISC complex containing AGO that guides target regulation [5, 7]. However, specific members of the DCL and AGO family of proteins are required in the biogenesis of each different type of siRNA. For instance, RDR2 and DCL3 are preferentially used in the biogenesis of hc-siRNA originating from repetitive regions, and AGO4 is required for its function [16–18]. Repeat-associated siRNA is involved in silencing transposons and other repeat elements by methylation of DNA , resulting in epigenetic modifications that mediate gene silencing .
Small RNA has been implicated in the interaction between leguminous plants and nitrogen-fixing bacteria [21, 22]. Gramineous plants also establish association with endophytic diazotrophic bacteria, which colonize intercellular spaces and vascular tissues of plants without causing damage to the host plant [23–25]. However, the role of sRNA in the grass-diazotrophic bacteria interaction has not been described. Maize is one of the world’s most widely cultivated crops, valuable not only for human and animal consumption, but also for ethanol production . Previous studies showed that maize interacts with endophytic diazotrophic bacteria, including Herbaspirillum spp. and Azospirillum spp. [27, 28]. Furthermore, inoculation with diazotrophic bacteria increases maize productivity, demonstrating the benefits of these bacteria for the plant . In addition to its economic importance and the successful interaction with diazotrophic bacteria, maize has several advantages as a grass-model for the analysis of plant-diazotrophic bacteria association by sRNA regulation: its genome is sequenced to a high quality ; recent studies have shown that maize sRNA is regulated in response to changes in the environment; and a strong epigenetic regulation occurs in maize due to the high abundance of transposable elements (TE) in the genome [31–33].
In order to understand the roles of sRNA in maize during the interaction with endophytic diazotrophic bacteria, sRNA libraries from maize hybrids (Zea mays – UENF 506-8) inoculated with H. seropedicae were constructed and sequenced. The analysis uncovered a dynamic regulation of known and novel miRNA in plants inoculated with H. seropedicae. Expression analysis in biological replicas and in plants inoculated with another diazotrophic bacteria, A. brasilense, showed that the expression of four copper-regulated miRNAs increased in the presence of the bacteria. Targets of that miRNA are involved in copper homeostasis and in defense pathways against pathogenic microorganisms, suggesting that maize colonization by diazotrophic bacteria is facilitated by the attenuation of defense mechanisms. Also, our analysis identified novel miRNA mapping to transposable elements (TE). Additional analysis identified siRNA that matched small regions close to either the 5′ or 3′ ends of coding DNA sequences (CDSs). A reduction in the transcript levels of the corresponding CDS was verified. Finally, an increase in GC and GHC methylation was observed in the same region, suggesting an epigenetic regulation in response to diazotrophic bacteria inoculation. Our findings suggest important roles for sRNA regulation in maize during association with beneficial endophytic diazotrophic bacteria and could assist breeding programs to develop maize or other grasses more efficiently in association with diazotrophic bacteria, which would result in an improvement of crop production.
Maize inoculation with diazotrophic bacteria
Computational identification of sRNA from library data
Summary of results obtained from bioinformatics analysis of each small RNA library
Changes in abundance of known maize miRNA during association with endophytic diazotrophic bacteria
Differential expression of conserved miRNAs
Log 2 (Hs/CT)
To confirm the miRNA regulation, two more libraries were constructed and sequenced using biological replicates (experiment B) and analyzed as above. These libraries, denominated CTb and Hsb, had 5,137,415 and 2,159,935 non-redundant reads filtered, respectively. The patterns of differential expression of 25 miRNA families identified are available in Additional file 1: Table S1. Comparison between the results from libraries in experiments A and B showed that 15 miRNAs shared the same regulation profile, while 10 miRNAs had contrasting profiles. Interestingly, miR398 and miR408 were up-regulated in both analyses.
Cu-miRNAs are up-regulated in response to diazotrophic bacteria
Identification of novel maize miRNA
New miRNAs identified
Length of hairpin precursor
RPM - CT
RPM - Hs
In addition to the precursor analysis, the length and the abundance of new mature miRNA was also examined. The majority of the novel miRNAs are 24 nt in length (9 out 15 sequences), four were of 21 nt and two were of 22 nt. To compare the expression of novel miRNA, we used the same approach described for expression analysis of known miRNA. Eleven new miRNAs were identified in the inoculated sample, three of which were also found in the control library but at lower levels. Four novel miRNAs were exclusive to the control library (Table 3). Next, their putative targets were predicted using psRNA target. A total of 131 putative targets for the 15 mature new miRNAs were identified (Additional file 1: Table S1). However, more than 87% of the putative targets are uncharacterized genes. Therefore, the molecular function of these novel miRNAs is unknown.
Novel miRNAs mapped at Transposable Elements
siRNA production derived from repeats and CDSs
Recently, plant sRNA regulation has been shown to play important roles in plant development, nutrition homeostasis, response of abiotic stress and the plant-microbe interaction, including interaction with pathogens, and in rhizobia-legume symbiosis [45–48]. One characteristic of the association of leguminous plants and rhizobia bacteria is the development of structures called root nodules, where bacteria establish and contribute to the plant with biologically fixed nitrogen . Endophytic nitrogen-fixing bacteria have also been isolated from gramineous plants. However, in grasses, the diazotrophic bacteria are found colonizing intercellular spaces and vascular tissues of most plant organs, without forming any particular structure [24, 49]. Although several studies have described the benefits of grass-diazotrophic bacteria interactions and the molecular pathways involved in this association [50–52], little is known about the role played by sRNA in response to colonization by endophytic diazotrophic bacteria in grasses, like maize. One study has shown that the maize hybrid line UENF 506-8 has an efficient association with diazotrophic bacteria ; this hybrid, therefore, was used in the present study.
The main categories of plant regulatory sRNA are miRNA and siRNA . Our analysis identified a set of maize miRNA and siRNA regulated by the association of the plant with diazotrophic bacteria. Maize sRNA libraries made from seedlings inoculated for seven days with the endophytic diazotrophic bacteria H. seropedicae (HRC54) and control seedlings were constructed and sequenced. The distribution profile of sequenced sRNA showed that the most abundant and most complex fraction was the sRNA of 24 nt in length, followed by 22, 23 and 21 nt, in agreement with published reports of maize small- RNA libraries [54–56].
Based on characteristics of plant miRNA conservation, 25 miRNA families were identified in the analysis. Among the miRNA most expressed in plants inoculated with H. seropedicae, miR159 and miR168 were also identified as being regulated in soybean nodules , suggesting a role for these miRNAs in the association of diazotrophic bacteria with plants. Interestingly, these miRNAs were previously characterized as miRNA modulated in response to pathogen infection. MiR159 was up-regulated in Arabidopsis inoculated with Pseudomonas syringae , as well as in maize inoculated with beneficial bacteria. In contrast, the miR393 expression profile in response to diazotrophic bacterial inoculation was different from that observed in a pathogenic infection. MiR393 was the first miRNA described to be involved in the regulation of plant immunity . This miRNA was induced in plants infected with Pseudomonas syringae, contributing to antibacterial resistance [57, 59]. On the other hand, in maize inoculated with diazotrophic bacteria, a repression of miR393 was observed, suggesting that in the presence of H. seropedicae, the defense response through the miR393-based regulation pathway was not activated.
More recently, miR397 has been shown to be involved in nitrogen fixation-related copper homeostasis in Lotus japonicus . MiR397 was classified as Cu-miRNA, because its target is an mRNA that encodes laccase protein involved in copper homeostasis. In maize, four Cu-miRNAs - miR397, miR398, miR408 and miR528 - were up-regulated and their targets were down-regulated in response to H. seropedicae inoculation. There are canonical targets described for these miRNAs and the cleavage of these targets by their respective miRNAs was previously confirmed using RACE 5′ PCR [60–62]. Copper is an important micronutrient and serves as a cofactor for proteins involved in important pathways, among them photosynthesis and the metabolism of scavenging reactive oxygen species . In plants, targets of other evolutionarily conserved miRNA encode genes involved in copper homeostasis, such as laccase, copper superoxide dismutase (CSD) and cupredoxin . The described targets of miR397, miR408 and miR528 in maize are laccases and cupredoxins , important copper protein families with redox activities  whose domains are conserved in other enzymes . More so, in maize, cupredoxins are involved in oxidative stress response signaling, mediating electron transfer or oxidation homeostasis during stress . Biotic stress causes accumulation of reactive oxygen species as an early response to pathogen attack . The oxidative burst can result in the direct death of pathogens, acting as a mechanism of plant defense . Previous work has shown that miR408, after 14 h, is repressed in Arabidopsis plants inoculated with the pathogenic bacteria, Pseudomonas syringae pv. Tomato, while its target was induced , suggesting that biotic stress can trigger down-regulation of Cu-miRNA, increasing the steady-state of their targets, generating a burst of oxidative stress. In plants inoculated with endophytic diazotrophic bacteria, an inverse miRNA/target regulation was observed: miR397, miR408 and miR528 were induced, and their targets were repressed. These results suggest that H. seropedicae does not activate the early defense response against bacterial colonization in maize. A similar regulation of these miRNAs occurs in plants inoculated with A. brasilense. Furthermore, an additional role for miR408 in plant/beneficial interaction might be to reduce lignin biosynthesis as a consequence of decreased laccase activity , facilitating colonization by endophytic bacteria.
Copper superoxide dismutase is responsible for removing reactive O2 species (ROS), reducing oxidative stress . Superoxide dismutase is the first line of defense to convert this reactive oxygen species ; accordingly, during pathogenesis, CSD accumulates due to the repression of miR398 expression [72, 74]. In contrast, the up-regulation of miR398, and consequently, the repression of its target, suggests once more that beneficial endophytes such as H. seropedicae and A. brasilense are not recognized as pathogens by maize and therefore do not trigger defense responses such as ROS production.
A subset of miRNA is considered non-conserved if it is present only in certain plants or in closely related species [75, 76]. The miR528, for instance, is an example of monocot-specific miRNA . Non-conserved miRNA is the result of emerging classes of lineage-specific families, and it originated from recently evolved MIR genes . Here, we have identified 18 bona fide precursors of novel miRNAs, which obey all the rules established for identification of new microRNA, including the identification of miRNA and miRNA* sequences in the same library. The majority of these new miRNAs are 24-nt species, longer than canonical 21-nt miRNA . A recent study proposed that miRNA with 24 nt is derived from precursor cleavage by DCL3 and that its biogenesis is similar to that of siRNA [80, 81]. Because these novel miRNAs had not been identified in other plants, they probably have emerged recently as lineage-specific miRNA. The evolution of miRNA genes has been widely discussed and two hypotheses for miRNA birth have been postulated: miRNA genes could originate from inverted gene duplication  or randomly from repetitive elements present in the genome [83, 84]. In support of the last model, a recent study revealed the co-localization of maize miRNA within TE sequences . Furthermore, analysis of 163 miRNAs evolving from repetitive elements in four plants, Arabidopsis, poplar, rice and sorghum, demonstrated that a considerable number of young miRNA identified were species-specific . In our study, a subset of the novel miRNA identified was characterized as repetitive element-related miRNA, suggesting that they are young miRNA. Although the targets of the novel miRNAs have not been determined, most of these miRNAs are induced in response to plant-diazotrophic bacteria association and their targets could play a role in the plant’s interaction with diazotrophic bacteria.
More frequently in plants, the number of miRNA families related to TE is smaller than the number of miRNA families not related to TE . However, TEs are highly abundant in maize, comprising more than 80% of the genome . Repeat-associated siRNA has been identified in maize, especially siRNA matching retrotransposons. This corroborated data that showed that the maize genome has more retrotransposons than DNA transposons, with Gypsy being the most frequent class . The majority of siRNAs derived from TE have 24 nt followed by 22-nt species. Repeat-associated siRNA is most commonly of 24 nt, and recent studies have suggested that RDR2 and DCL3 are required for the biogenesis of this siRNA class, while 24 nt guided-DNA methylation is dependent on DCL4 [5, 17, 18]. Additionally, there is evidence of other mechanisms involved in the production of siRNA from repeats, inferred from an enrichment of 22-nt siRNA that was seen in the MOP1 mutant, an ortholog of RDR2 . In plants, despite the existence of many TEs, they are usually inactive. SiRNA could be a tool for controlling their own TE precursors, acting as a feedback mechanism . Interestingly, TEs are activated in response to stress, including pathogen infection, mechanical stress or abiotic stress [89, 90]. Accordingly, TEs are demethylated during pathogen infection in Arabidopsis, relevant because TE demethylation is thought to take part in the plant defense genes’ activation . On the other hand, several siRNAs from TEs were identified only in the inoculated library, suggesting that siRNA may also have an important role in TE silencing, resulting in a more efficient plant association with beneficial bacteria. Based on this, it is possible to propose that plants can sense pathogenic and beneficial microorganisms differently and trigger specific epigenetic-mediated regulatory mechanisms.
It has been shown that siRNA that match protein-coding genes can regulate gene expression [17, 92]. In this study, genes with a large number of siRNA aligned with their CDSs were identified, five among them with more than 1,000 unique siRNA reads. Although, these genes are classified as unknown, the abundance and complexity of the siRNAs mapping onto these genes suggest that its silencing could be important for diazotrophic bacteria association, given that more siRNAs were identified in the inoculated sample. GRMZM2G037875_T03 is the CDS with greatest number of unique siRNAs aligned with it. Interestingly, a hotspot of mapped siRNAs is located at the 3′-end of the CDS, a region that is exclusive to one splice variant of GRMZM2G037875. In contrast, for another CDS, GRMZM2G487629_T02, siRNAs were aligned at the 5′-end. According to a recent study in Arabidopsis, siRNA related to protein-coding genes can be generated by the RDR2-DCL3 pathway, but the mechanism that regulates gene expression of protein-coding genes by siRNA is not well understood . One hypothesis is that the siRNA is loaded onto AGO4-containing complexes to guide methylation of target genes. Accordingly, the gene regions enriched for siRNA are also enriched in sites of CG and CHG methylation . For two CDSs (GRMZM2G037875_T03 and GRMZM2G487629_T02), the results suggested that siRNA can mediate the DNA methylation. Also, the majority of maize siRNA that aligned in this CDS is 24 nt in length, corroborating the hypothesis that 24 nt siRNA triggers DNA methylation . DNA methylation at the 5′ or 3′-end has been correlated with the silencing of genes, consequently leading to the reduction of gene transcription [94, 95]. Interestingly, the levels of GRMZM2G037875_T03 transcript were reduced in transcriptome analysis of plants inoculated with H. seropedicae, suggesting that this splice variant was methylated by siRNA, leading to a decreased transcription. This information can help to understand the regulation of this siRNA class; however, further studies should be performed to uncover the function of the genes, in particular the role of the splice variant that is enriched in the plants inoculated with diazotrophic bacteria.
Relatively little is known about plant epigenome mechanisms involved in the plant response to diazotrophic bacteria. Our results show that plants may use a variety of sRNA regulation mechanisms to regulate and favor this association, and that the mechanisms activated are in contrast with the ones previously described for pathogen infection. In conclusion, our data suggest that maize, and possibly other grass species, have RNA-based silencing mechanisms that can trigger specific responses when plants interact with microorganisms to establish either a beneficial association or to fight pathogenic infection.
Plant material and diazotrophic bacteria inoculation
Maize seeds of the hybrid UENF 506-8 were surface-sterilized for 15 min with a 10% (v/v) solution of commercial bleach containing 5.25% (w/v) NaCl, then washed several times with distilled water. After soaking overnight in distilled water, seeds were germinated at 25°C in wet paper. Seven days after germination, seedlings were transferred to a 0.5x Hoagland’s solution  in a growth chamber at 24°C with a 10 h photoperiod and left for two weeks. The Hoagland’s solution was renewed every 3 or 4 days. After this period, seedlings were inoculated with two diazotrophic bacteria, A. brasilense (BR11005) and H. seropedicae (HRC54), as described by James et al. . Suspensions (150 uL) containing 10-6 to 10-7 diazotrophic bacteria were added to each 30 mL of the plant growth medium. Control plants were mock inoculated. Seven days after inoculation, whole plants were harvested, bacteria colonization was evaluated by the Most Probable Number (MNP) estimation , and quickly frozen in liquid nitrogen. Four experiments were performed, of which two were used for Illumina sequencing, while the other two were used to validate the sequencing analysis. Total RNA was isolated from whole plants using Trizol (Invitrogen, CA, USA) as described by the manufacturer. RNA purity was analyzed using a Thermo Scientific NanoDrop™ 2000c spectrophotometer and the RNA integrity was verified by electrophoresis on a 1% agarose gel.
Construction and analysis of small RNA libraries
Two sRNA libraries made from control maize hybrid (UENF 506-8) seedlings and seedlings inoculated for seven days with diazotrophic bacteria, H. seropedicae (HRC54) were constructed and sequenced; two biological replicas of each library were sequenced. Total RNA (~10 μg) from control and H. seropedicae inoculated plants was sent to Fasteris Life Sciences SA (Plan-les-Ouates, Switzerland) for small RNA library construction and subsequent sequencing by Illumina technology. Quality of the sequences was evaluated by measurement of the quality of the reads according to the percentage of bases having a base quality greater than or equal to 30 (Q30). On average, 80% of each channel had Q30 quality. Next, 3′ Illumina adapters (CTGTAGGCACCATCAAT) and “N” bases trimmed of the reads and sequences within the 18-28-nt range were separated for further analysis.
After trimming and filtering, the remained reads were subjected to the University of East Anglia (UEA) sRNA toolkit (Plant version) miRProf, which allows the selection of conserved mature miRNA and provides the miRNA expression profile. The sRNA libraries data have been submitted to NCBI - Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE47886. The miRProf was run with sRNA of minimum size 18 nt, maximum size 28 nt. This tool matches sRNA libraries with known Viridiplantae mature miRNA deposited in miRBase database release 19 (http://www.mirbase.org/ftp.shtml), using a PatMaN program. The output of the miRProf showed sequences of miRNA that had at most one mismatch with the miRBase database and contained information about total and non-redundant sequence counts. To allow comparison between libraries, counts were normalized. Normalized counts are given in reads per 1 million (RPM) and the total reads after the final trimming and filtering steps were used for normalization. The fold changes were calculated by l log2 (Hs/CT). The statistical analysis (Fisher exact test) was performed with a p-value cutoff < 0.05 and Bonferroni correction.
Novel miRNAs were identified in the maize libraries using the UEA sRNA toolkit (Plant version) miRCat pipeline. Sequences were mapped to the maize genome (B73 RefGen_v2) to find clusters of sRNA. The most abundant sRNA read within a cluster was chosen as the likely miRNA candidate. Only new miRNA candidates with a corresponding miRNA* were further analyzed. The flanking sequences surrounding the sRNA were extracted from the genome using a 75-nt window length. Each sequence window was then folded using RNAfold. The precursors of the miRNA candidates were tested using randfold (using a cutoff of 0.1), and an additional minimal folding free energy index (MFEI) was calculated according to Zhang et al. . In order to be classified as novel miRNA, candidate sequences were searched against miRBase database release 19 using standalone BLAST , with default parameters. The folding structures of the new miRNA precursors identified were obtained with the UEA sRNA toolkit-RNA hairpin folding and annotation tool, which uses the Vienna Package to obtain the secondary structure of a precursor sequence, highlighting the miRNA/miRNA* sequences on the hairpin structure. Next, these precursors were mapped in the maize genome using BLASTn at MaizeGDB (http://popcorn.maizegdb.org/main/index.php) and a CViT image of the B73 assembly was created using information from the Maize Genome Sequencing Consortium . Additional analyses were performed on the MaizeGDB website to compare the precursor of novel miRNA against TEs from the Maize Transposable Elements Database (http://maizetedb.org/~maize/).
Prediction of miRNA targets
To identify the putative miRNA targets, we used the Plant Small RNA Target Analysis Server, psRNA Target (http://plantgrn.noble.org/psRNATarget/). In this investigation, we used the maize genome sequence - B73 RefGen_v2, and the following parameters: maximum expectation less than 3.0; 20 bp of length for complementarity scoring; target accessibility equal to 25; flanking length around target site for target accessibility analysis was 17 bp in upstream and 13 bp in downstream; and range of central mismatch leading to translational inhibition was 9-11 nt.
In order to obtain a functional characterization of the putative targets of conserved miRNA, the maize genome locus for each target was submitted to agriGO . The singular enrichment analysis (SEA) was performed to find enriched GO terms within annotated miRNA targets.
Characterization of siRNA candidates
After the identification of miRNAs (conserved and novel), the remaining sRNAs were classified as siRNA candidates. The classification of these siRNAs was performed using two approaches: the identification of siRNA related to repeats, and siRNA related to CDSs (Coding DNA Sequences). Both analyses used the program Bowtie, release 0.12.9 , to align the siRNA candidates against specific databases. Only the best reads were selected and three mismatches were allowed. In the first alignment, we used sequences of maize repeats from the Repbase, v.18 ; and in the second, we used maize CDS dataset of the B73 RefGen_v2. From CDSs aligned, we selected two genes that had the largest numbers of matches to non-redundant siRNA. The alignment files were converted to bam using SAMtools  and siRNA matches in maize CDS were quantified in Artemis.
Additional analyses were performed in Cold Spring Harbor Laboratory using their maize methylation database to identify the methylation sites in two CDS regions (GRMZM2G037875_T03 and GRMZM2G487629_T02). The identification of maize transcripts was done in the maize transcriptome database available in our laboratory. The mRNAseq was performed using the same samples used for the construction of the sRNA libraries.
Validation of bioinformatics analysis by qRT-PCR
The expression profiles of four Cu-miRNAs (miR397, miR398, miR408 and miR528) were assayed by stem–loop qRT-PCR [105, 106]. Total RNA extracted from two independent experiments of plants inoculated with A. brasilense, H. seropedicae and control plants was treated with DNaseI (Promega). Total RNA was then reverse transcribed into cDNA using Super-ScriptIII reverse transcriptase (Invitrogen). In the same reaction, RT primers specific for each miRNA sequence and random primers were used to enable the amplification of constitutive genes and of the miRNA targets. With this cDNA, qRT-PCR was used with SYBR Green PCR Master Mix (Applied Biosystems). To each well, 1 μL of first strand cDNA, 5 μL of SYBR Green solution, 2 μL of the forward primer (10 μM) and 2 μL of reverse primer (10 μM), designed as described in the protocol , were added. Two housekeeping genes were used as internal controls: Ubiquitin (F/5′ AGACCCTGACTGGAAAAACC 3′; R/5′ CGACCCATGACTTACTGACC 3′) and Actin (F/5′ CAATGGCACTGGAATGGT 3′; R/5′ ATCTTCAGGCGAAACACG 3′). qRT-PCR was performed using Applied Biosystems 7500 Real-Time PCR Systems. In the expression analysis of miRNA targets, the following primers were used: miR397 target (F/5′ GTTCGATGTGCAAATGACCAA 3′; R/5′ CCGTCACGATGCTCTTGCT 3′), miR398 target (F/5′ TCTCATTATTCTCATGTGTTCTCAGTTC 3′; R/5′ CGGCGACGGCAACAAG 3′), miR408 target (F/5′ CCAAGAGACGCCAGTGAAGAG 3′; R/5′ TACTGCCCGTTCACCGTGAT 3′) and miR528 target (F/5′ CCCAGCACTCATTCCATAGCA 3′; R/5′ CCCAGCACTCATTCCATAGCA 3′).
The data set supporting the results of this article is available in the NCBI - Gene Expression Omnibus repository, (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE47886.
We are grateful to Dr. Messias Gonzaga Pereira, Universidade Estadual do Norte Fluminense (UENF), for providing maize seeds, and EMBRAPA Agrobiology for providing Azospirillum brasilense (BR11005) and Herbaspirillum seropedicae (HRC54) strains. Research by our group is supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Instituto Nacional de Ciência e Tecnologia em Fixação Biológica de Nitrogênio (INCT), Financiadora de Estudos e Projetos (FINEP), Fundação de Amparo à Pesquisa do Rio de Janeiro (FAPERJ) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). We thank Dr. Martha Sorensen and André Ferreira for language editing.
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