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Annals of Botany logoLink to Annals of Botany
. 2008 Jul 31;102(4):509–519. doi: 10.1093/aob/mcn129

Submergence-responsive MicroRNAs are Potentially Involved in the Regulation of Morphological and Metabolic Adaptations in Maize Root Cells

Zuxin Zhang 1,3,*, Liya Wei 1, Xilin Zou 2, Yongsheng Tao 1, Zhijie Liu 2, Yonglian Zheng 2,*
PMCID: PMC2701776  PMID: 18669574

Abstract

Background and Aims

Anaerobic or low oxygen conditions occur when maize plants are submerged or subjected to flooding of the soil. Maize survival under low oxygen conditions is largely dependent on metabolic, physiological and morphological adaptation strategies; the regulation mechanisms of which remain unknown. MicroRNAs (miRNAs) play critical roles in the response to adverse biotic or abiotic stresses at the post-transcriptional level. The aim of this study was to understand submergence-responsive miRNAs and their potential roles in submerged maize roots.

Methods

A custom μParaflo™ microfluidic array containing plant miRNA (miRBase: http://microrna.sanger.ac.uk) probes was used to explore differentially expressed miRNAs. Small RNAs from treated roots were hybridized with the microarray. The targets and their cis-acting elements of small RNA were predicted and analysed by RT-PCR.

Key Results

Microarray data revealed that the expression levels of 39 miRNAs from nine maize and some other plant miRNA families were significantly altered (P < 0·01). Four expression profiles were identified across different submergence time-points. The zma-miRNA166, zma-miRNA167, zma-miRNA171 and osa-miRNA396-like were induced in the early phase, and their target genes were predicted to encode important transcription factors, including; HD-ZIP, auxin response factor, SCL and the WRKY domain protein. zma-miR159, ath-miR395-like, ptc-miR474-like and osa-miR528-like were reduced at the early submergence phase and induced after 24 h of submergence. The predicted targets for these miRNAs were involved in carbohydrate and energy metabolism, including starch synthase, invertase, malic enzyme and ATPase. In addition, many of the predicted targets were involved in the elimination of reactive oxygen species and acetaldehyde. Overall, most of the targets of induced miRNAs contained the cis-acting element, which is essential for the anaerobic response or hormone induction.

Conclusions

Submergence-responsive miRNAs are involved in the regulation of metabolic, physiological and morphological adaptations of maize roots at the post-transcriptional level.

Key words: Anaerobic metabolism, Zea mays, gene expression, transcription factor, microRNA, flooding stress

INTRODUCTION

The regulation of gene expression in response to environmental cues is an important factor in plant survival and adaptability. Both transcriptional and post-transcriptional mechanisms have been implicated in the control of nuclear gene expression in response to submergence or flooding stress (Dennis et al., 2000; Dolferus et al., 2003). Transcriptome data have shown that the expression levels of a number of genes are altered in cells of submerged roots. These genes are involved in a broad spectrum of biochemical, cellular and physiological processes, including glycolysis, energy metabolism, lipid metabolism, signal transduction, DNA transcription, protein biosynthesis and digestion, cell components and photosynthesis (Klok et al., 2002; Liu et al., 2005; ZX Zhang et al., 2005, 2006). Many anaerobically induced genes share a consensus sequence called the anaerobic-responsive element (ARE), which is located in the promoter regions. The ARE is found to contain all the sequences necessary for both anaerobic induction and the binding of the transcription factors (TFs) of the Myb family (Walker et al., 1987; Dolferus et al., 1994; Hoeren et al., 1998). The data from the proteome and the bioactivity of functional proteins showed that the proteins efficiently synthesized in oxygen-deprived roots include enzymes involved in the breakdown of sucrose, glycolysis, ethanolic fermentation, aerenchyma formation and, especially, anaerobic polypeptides (Sachs et al., 1980, 1996; Andrews et al., 1994; Olson et al., 1995; Chang et al., 2000). A few of the protein products, especially some of the aerobic polypeptides (APs), did not increase while their mRNAs accumulated in oxygen-deprived cells. One potential cause of this is that the accumulated transcripts encoding these enzymes and anaerobic polypeptides are selectively translated, but not the APs. This indicates that the selected syntheses of anaerobic polypeptides are involved in transcriptional, as well as significant post-transcriptional regulation of gene expression (Fennoy and Bailey-Serres, 1995; Fennoy et al., 1998).

Plants exhibit a wide variety of anatomical, morphological and physiological responses to submergence in the roots or the whole plant. Some appear to have significant adaptability. The most conspicuous anatomical responses of maize roots to submergence, or anoxia, are the formation of an extensive aerenchyma system in the cortex and the development of adventitious roots in the vicinity of the cotyledonary nodes. These greatly facilitate gas transport in submerged root systems (Armstrong et al., 1971). Another response in leaves is stomatal closure. These changes can be mediated by diverse phytohormones, with ethylene and abscisic acid (ABA) playing prominent roles (Liao and Lin, 2001). Recently, Sub1A, a flooding-tolerance gene, was cloned in rice (Xu et al., 2006). The gene encodes a TF belonging to the B-2 subgroup of the ethylene-response factors, its expression increases the transcription of genes associated with ethanolic fermentation and represses the transcription of genes associated with cell elongation and carbohydrate catabolism. Regulation of genes involved in the morphological and physiological responses to oxygen deprivation, however, remains uncharacterized.

MicroRNAs (miRNAs) are approx. 21-nt-long, non-coding RNAs that play critical roles in the regulation of gene expression at the post-transcriptional level. Plant miRNAs regulate many genes involved in developmental control (Bonnet et al., 2004; Jones-Rhoades and Bartel, 2004), organ polarity (Eshed et al., 2001; McConnell et al., 2001; Kidner and Martienssen, 2004), development transitions (Aukerman and Sakai, 2003; Chen, 2004), leaf growth (Palatnik et al., 2003) and RNA metabolism (Xie et al., 2003). Recently, BH Zhang et al. (2005) found that >25 % of ESTs contain miRNAs in stress-induced plant tissues. It suggested that miRNAs may play an important role in plant responses to environmental cues. Several specific stress-responsive miRNAs have been identified under nutrient deficiency (Jones-Rhoades and Bartel, 2004; Fujii et al., 2005; Chiou et al., 2006), drought, cold and salinity stress (Sunkar and Zhu, 2004; Zhao et al., 2007), UV-B radiation (Zhou et al., 2007) and mechanical stress (Lu et al., 2005). Submergence is a serious abiotic stress to maize seedlings. In this study, a custom μParaflo™ microfluidic array (LC Sciences, Houston, TX, USA) containing version 10·0 plant miRNA probes was used to reveal the response of miRNAs to submergence-stress. The results indicated that these responsive miRNAs potentially play a vital role in the regulation of the morphological and metabolic adaptation response in cells of submerged roots of maize.

MATERIALS AND METHODS

Plant treatment and RNA isolation

Mo17, an inbred line of Zea mays sensitive to submergence, was germinated in an incubator at 30 °C. Uniformly germinated seeds were then sown in pots filled with vermiculite and grown until the seedlings developed three leaves in an incubator at 30 °C with a photosynthetic photon flux density of about 200 µmol m−2 s−1 immediately above the seedlings and 14/10 h light/dark cycles. During this period, the seedlings were irrigated every 2 d with 1× growth culture solution [Ca(NO3)2 820·7 mg L−1, KNO3 505·6 mg L−1, MgSO4·7H2O 616·2 mg L−1, KH2PO4 272·2 mg L−1, Fe-EDTA 13·02 mg L−1, H3BO3 2·860 mg L−1, MnSO4 1·015 mg L−1, CuSO4·5H2O 0·079 mg L−1, ZnSO4·7H2O 0·220 mg L−1, H2MoO4 0·090 mg L−1]. Seedlings with three leaves were used in all experiments. For the submergence treatment, seedlings were submerged with fresh culture solution, leaves were two-thirds underwater (i.e. the uppermost one-third of the shoot remained in air), and the roots were harvested at 12, 24 and 36 h post-treatment. Untreated seedlings were used as controls. About 2 g roots were collected from each treatment, washed free from vermiculite for approx. 30–60 s, immediately frozen in liquid nitrogen, and then ground into a fine powder. The total RNA from each sample was extracted using the Trizol reagent (Invitrogen, USA).

miRNA microarray and hybridization

Microarray assays were performed using a service provider by LC Sciences. A custom μParaflo™ microfluidic chip containing 623 unique plant probes from version 10·0 representing 799 miRNAs of 13 plant species miRNAs, with each chip containing five probe sets (Sanger Institute, Cambridge, UK; http://microrna.sanger.ac.uk/sequences/; Griffiths-Jones et al., 2006) was used. The 799 miRNAs consisted of 154 from Arabidopsis thaliana, 115 from Oryza sativa, 39 from Sorghum bicolor, 31 from Triticum aestivum, 10 from Saccharum, 43 from Zea mays and 407 from seven other plant species. PUC2-20B, a non-homologous nucleotide acid, and 5S rRNA served as positive controls. Blank cells and nucleic acid probes that were non-homologous with the sample RNA were also designed for the microarray and used as negative controls. No less than 5 µg of total RNA sample was used as the starting material for each assay. RNAs were size-fractionated using a YM-100 Microcon centrifugal filter (Millipore, Bedford, MA, USA), and the small RNAs (<300 nt) isolated were subsequently 3′-extended with a poly(A) tail using poly(A) polymerase. Among the control probes, PUC2PM-20B and PUC2MM-20B were a perfect match and single-base mismatch probe of a 20-mer RNA positive control sequence, respectively, which was spiked into the RNA samples prior to labelling. The oligonucleotide tag was then ligated to the poly(A) tail for later fluorescent dye staining; two different tags were used for the two RNA samples used in the dual-sample experiments. Briefly, purified small RNAs were labelled with Cy3 or Cy5 fluorescent dyes (control and submergence-treatment, respectively) and then hybridized to the dual-channel microarray. The hybridization buffer was 100 µL 6× SSPE buffer (0·90 m NaCl, 60 mm Na2HPO4, 6 mm EDTA, pH 6·8) containing 25 % formamide at 34 °C. Microarray experiments were performed three times using distinct biological samples. Hybridization images were collected using a laser scanner (GenePix 4000B; Molecular Devices, Sunnyvale, CA, USA) and digitized using the Array-Pro image analysis software (Media Cybernetics, Bethesda, MD, USA). Data were analysed by first subtracting the background and then normalizing the signals using a LOWESS filter (locally weighted regression). In the two-colour experiments, the ratio of the two sets of detected signals was log2 transformed and balanced, and the P-values of the t-test were calculated. The difference of detected signals was considered significant at the 1 % level of significance.

miRNA target prediction and cis-acting element analysis

An miRNA is a transcript encoded by an miRNA gene. Theoretically, pre-miRNA sequences should be exact matches with specific maize genomic sequences. To determine the miRNA genes, each pre-miRNA sequence, which can be obtained by query at http://microrna.sanger.ac.uk/sequences/, was aligned to the maize genome sequence (maizesequence.org or maize.tigr.org). The DNA segment flanking queried sequences of not less than 10·0 kb was obtained, and used to predict the open reading frame using FGENESH (http://mendel.cs.rhul.ac.uk/). If the pre-miRNA sequence matched with a predicted gene sequence (including exon, intron and probable 5′- and 3′-terminal sequences), the DNA segment was regarded as an miRNA gene sequence. Since plant miRNAs recognize their target mRNAs by near-perfect base pairing, computational sequence similarity searches were used to identify potential targets. For the prediction of miRNA target mRNAs, a web-based integrated computing system, miRU, was queried using mature miRNA sequences, all potential complementary sequences containing limited mismatches were selected (Y Zhang, 2005). If miRNAs did not pair with any hit in miRU, then the miRNA and its reverse complementary sequence was used as a query in the public maize EST database (www.maizesequence.org). The number of mismatches was limited to less than three nucleotides; insertions or deletions were permitted to consist of no more than one nucleotide; and no more than five G-U pairs were admitted. The predicted target EST sequences were aligned with ClustalW. New contigs were then aligned and used for BLAST searching for functional annotation and for genomic sequence queries, respectively. The 1500-bp DNA sequence upstream of the transcription initiation site of each predicted miRNA gene and target gene was truncated to identify cis-acting motifs using PlantCARE (Rombauts et al., 1999; Lescot et al., 2002).

The expression assay of target genes

From each sample, 10 µg of total RNA was incubated with two units of RNase-free DNase I (New England BioLabs, Inc.) to remove DNA contamination from the RNA. An oligo(dT) DNA primer was then added to conduct the reverse transcription reaction as follows: 0·5 µL of total RNA and 1·75 µL of DEPC-free H2O were denatured for 5 min at 70 °C then incubated on ice for 3 min. The following reagents were then added in order: oligo(dT) DNA (0·25 µL of 2 µm), dNTP (0·5 µL of 10 mm each), RT buffer (1 µL of 5 × ), SuperScript II reverse transcriptase (0·25 µL of 200 U μL−1), RNase inhibitor (0·25 µL of 40 U μL−1) and DEPC-free H2O (0·5 µL). The reaction mixture was incubated for 60 min at 42 °C to synthesize cDNA. The specific target gene primers were then added to amplify the target genes from the cDNAs, and γ-tubulin was selected as the endogenous reference. The name, accession and primer sequences of target genes are listed in Table 1.

Table 1.

The accessions of target genes and primers for RT-PCR

Target genes Accession Primer-sense Primer-antisense
Acyl-CoA thioesterase TC262881 GCATCCATTCGTCAGCCTTC TGATCCACGCTTCCCATCCC
AGO1-1 TC255055 AATGCCACAGTCATACCG TAACTCCCTTGTTGCTTGT
Auxin response factor 12 TC268913 GGGCAAGTCCATCAGAAT ACATCGTTCTCCCTGTCG
GAMYB TC269992 GTCAGCGTCCACCTTCTAC CATTGAGGACCCACCACT
HD-zip TC271068 CGTAGCCCTGTTCCATTAGTT TGTGCTGACAATCGCCTTTC
Phospholipase D TC253142 AGGGCTTACCTGCCTGTC TGCTTCCTCCACCTCTGC
Serine/threonine protein phosphatase TC270317 CTGGACGCAATTTATTCAGC CCCGACACCAACTACCTCTT
ZAG1 TC274797 ACGGCAGGATGTCTGAAACG CTGAAGGAGGCACTGGAGCA
Gamma-tubulin X83696 TGTCGTCCAACCTTACAACTCACT TCTCCAGGGTCCTCCATTCC

RESULTS

Submergence-responsive miRNAs in roots of maize

The microarray data showed that >100 expressed miRNAs had changed expression profiles owing to submergence treatment. These miRNAs were identified to be present in diverse families of plant species. In general, different plant species have similar mature miRNA sequences in the same miRNA families. They typically differ by only one to three nucleotides. For example, three members of pta-miR159 (pta-miR159a/b/c) from Pinus taeda have only one nucleotide difference with ptc-miR159d from Populus trichocarpa, and ptc-miR159d is homologous to zma-miRNA159c/d. The miRNA sof159e from Saccharum officinarum has two nucleotide differences with osa-miR159a from Oryza sativa which is homologous with zma-miRNA159a/b (Fig. 1). Thus, cross-hybridization among members from the same family and among orthologues across species could explain these microarray results. To refine the differentially expressed miRNAs, those miRNA members in the same family showing similar expression profiles were selected as the actual differentially expressed miRNAs. Four members of osa-miR166 (e, g, k and m) showed similar expression profiles. They were up-regulated after 12 h of submergence then down-regulated after 24 h of submergence. The miRNA osa-miR166 g is an orthologue of zma-miR166l and zma-miR166 m, osa-miR166 k is a homologue of zma-miR166j and zma-miR166 k. Thus it is suggested that the four identified zma-miRNAs were actually submergence-responsive miRNAs.

Fig. 1.

Fig. 1.

The similarity of sequences among miRNA members from different species. The miRNA in parentheses is the homologue of the miRNA before the parentheses. Shaded nucleotides show differences with zma-miRNA or its homologue. (–) indicates the absence of a nucleotide.

Although many differentially expressed miRNAs from arabidopsis and Oryza sativa have been identified, miRNAs are evolutionarily conserved throughout the plant kingdom (BH Zhang et al., 2006a), their microarray expression levels reflected the expression of their counterparts in maize. For example, the expression signal of pta-miR159a/b/c and sof-miR159e could have been attributed to hybridization with members of zma-miR159 and contributed to the change in the expression level of zma-miR159. In addition, non-homologous miRNAs with maize identified by microarray hybridization were suggested to be newly identified miRNAs in maize. A total of 39 miRNAs, about 6·26 % (39/623) of the probes on the microarray, were identified as submergence-responsive miRNAs at the 1 % level of significance (Table 2). Thirty out of the 39 miRNAs aligned with nine maize miRNA families, while the others corresponded to several members of miRNA families from three other plant species; these include ath-miR395, ath-miR854, ptc-miR474, osa-miR396 and osa-miR528.

Table 2.

Submergence-responsive miRNA families and members

miR family Members of identified miRNAs Orthology miRNAs across species Homologous miRNAs in Zea mays*
zma-miR159 ptc-miR159d/f zma-miR159c, zma-miR159d
osa-miR159a/e pta-miR159a/b/c, sof-miR159e zma-miR159a, zma-miR159b
zma-miR160 ath-miR160a zma-miR160a/b/c/d/e
osa-miR160e zma-miR160f
zma-miR162 zma-miR162 zma-miR162
zma-miR166 ath-miR166a ptc-miR166n/p zma-miR166a
osa-miR166e/g/k/m zma-miR166l/m, zma-miR166j/k
zma-miR166 sbi-miR166a zma-miR166b/c/d/e/f/g/h/i
zma-miR167 osa-miR167d zma-miR167e/f/g/h/i
zma-miR168 osa-miR168a/b ath-miR168a zma-miR168a, zma-miR168b
zma-miR171 osa-miR171b/h zma-miR171d/e/i/j/h/k
zma-miR171b/c zma-miR171b/c
zma-miR319 osa-miR319a ath-miR319c, pta-miR319 zma-miR319a/b/c/d
ptc-miR474 ptc-miR474a/b/c
ath-miR395 ath-miR395b ppt-miR395
osa-miR396 osa-miR396d
zma-miR399 osa-miR399a zma-miR399a/c
osa-miR528 osa-miR528
ath-miR854 ath-miR854a

* Homology of identified miRNAs by microarray hybridization with maize miRNAs was obtained by searching in miRBase version 10·0 (Sanger Institute, Cambridge, UK; http://microrna.sanger.ac.uk/sequences).

At the three treatment time-points, the different miRNAs showed different expression levels, and four predominant expression profiles were detected using clustering analysis (Fig. 2). The expression of 19 miRNAs was up-regulated during the early stage (0–12 h) of submergence, then recovered to normal levels during later stages. The expression of 12 miRNAs, however, was down-regulated during the early stage, and increased after 24 h of submergence. Seven out of 39 miRNAs were dramatically induced between 24 h and 36 h of post-submergence, but sbi-miR166a from Sorghum bicolor showed a particular expression profile. It was down-regulated at the 24-h time-point, and then up-regulated at the 36-h time-point. These results indicated that the expression of miRNAs was regulated at different time-points during the submergence process.

Fig. 2.

Fig. 2.

The clustering of differentially expressed miRNAs for roots submerged for 12, 24 or 36 h relative to controls. miRNA from maize roots under normal growth condition was used as the reference. The colour saturation reflects the magnitude of the log2 expression ratio (Cy5/Cy3) for each transcript. Red colour means higher transcript levels than the reference, whereas green means lower transcript levels than the reference.

The potential target genes of submergence-responsive miRNAs

Previous studies have demonstrated that miRNAs regulate gene expression by binding to targeted mRNA sequences by a perfect or near-perfect hybridization (BH Zhang, 2005). This facilitates the prediction of plant miRNA targets using a homology search. A total of 38 potential target genes were identified. These potential target genes are involved in a broad spectrum of metabolite, cellular, and physiological processes, such as carbohydrate, lipid and energy metabolism, transcription, signal transduction, cell defence and differentiation. Of the predicted targets, the expression profiles of eight genes, including three genes encoding TFs (HD-ZIP, ZAG1 and GAMYB-binding protein), two signalling components (serine/threonine protein phosphatase, phospholipase D), an auxin response gene (ARF12), a key player in microRNA pathways (AGO1-1) and a metabolic gene (Acyl-CoA thioesterase) were confirmed by RT-PCR. Their expression profiles showed the expected negative regulation pattern of the target gene by the miRNAs (Fig. 3).

Fig. 3.

Fig. 3.

RT-PCR of representative target genes of miRNAs at different time-points in maize roots. (A) The expression of miRNAs associated with targets, expressed relative to the control value. (B) RT-PCR of representative targets of miRNAs. RT-PCR was performed with primers specific for each of the target genes. RT-PCR of γ-tubulin cDNA was used as a positive control.

Based on their biological function, the predicted target genes could be classified into three categories. First, many miRNAs directly targeted various TFs involved in plant development and organ formation. Most of the TFs were described previously as known targets of miRNAs in arabidopsis, Oryza sativa and Zea mays (Llave et al., 2002; Juarez et al., 2004; Kidner and Martienssen, 2004). For instance, ZAG1, an AGAMOUS-like gene in maize, was detected as the target of zma-miR159c/d. HD-ZIP and the scarecrow-like family (SCL) mRNA were, respectively, predicted as the target of zma-miR166 and zma-miRNA171. The expression levels of the three TFs were negatively correlated with those of corresponding zma-miRNAs (Fig. 3). Some of the transcription factor/activator mRNAs, such as heat shock factors, ethylene response element-binding proteins, MADS-box proteins, AP2 domain proteins, leucine zipper and zinc finger proteins, were up-regulated in response to various regimes of oxygen deprivation in arabidopsis and maize (Klok et al., 2002; Gonzali et al., 2005; ZX Zhang et al., 2006). It was found that these TFs were also predicted targets of miRNAs (Table 3). Secondly, several targets of miRNAs, such as GAMyb and auxin response factors (ARF12, ARF17 and ARF25), are involved in phytohormone signal cascades (Table 3). Thirdly, several targets of miRNAs encode proteins that function in diverse metabolic pathways and are involved in various physiological processes. Interestingly, many targets were involved in the biosynthesis of cell wall metabolites and ATP, such as β-d-xylosidase, glycoside hydrolase, carbonate dehydratase, starch synthase, malic enzyme, invertase, ATPase and ATP sulfurylase (Table 3). Of these metabolic-associated targets, the anaerobic-induced expression of starch synthase, malic enzyme and invertase were confirmed on the transcriptional and protein level in maize roots (reviewed by Drew, 1997; Vartapetian and Jackson, 1997), indicating that submergence-responsive miRNAs may be involved in regulating the pathway of anaerobic metabolism.

Table 3.

Predicted target genes and motif of target genes in 5′ upstream sequences

MiR ID Accession of miRNA targets* Protein annotation e-value Predicted motif in 5′ upstream of target gene
Zma-miR159a, b AC186310·3 Serine/threonine protein phosphatase 4e-67 ARE, GARE-motif, HSE, LTR, MBS, TGA
AC199576·2-Contig94 GAMYB 4e-170 ABRE, ARE, LTR, MBS
zma-miR159c/d AC204211·2-Contig32 Ubiquitin isopeptidase 1e-78 ABRE, ARE, GC-motif, LTR, MBS, TCA, TGA
AC194290·2-Contig69 V-ATPase subunit D 6e-98 ARE, MBS, WUN
AC188029·2 ZAG1, AGAMOUS 3e-45 ABRE, ARE, GARE, GC-motif, MBS, TCA
zma-miR160f AZM5_84507 Alpha/beta fold family protein 1e-122 ABRE, ACE, ARE, LTR, MBS
zma-miR162 AC191256·2 DICER-LIKE1 4e-54 ABRE, DRE, LTR, TGA
zma-miR166l/m/j/k AC191059·3 Rolled leaf1, HD-ZIP 0·0 ABRE, EIRE, GC-motif, LTR, MBS, plant AP-2
zma-miR167e/f/g/h/i AC191413·2-Contig32 Auxin response factor (12, 17, 25) 0·0 ARE, HSE, MBS, TCA, WUN
AC194260·2-Contig18 Neutral invertase 0·0 ABRE, GARE, MBS, MBS, TCA, TGA
zma-miR168a/b AC194028·2-Contig34 Serine/threonine-protein phosphatase 4E-80 ABRE, GARE-motif, TCA
AC190578·3-Contig63 Leucine-rich repeat family protein 0·0 GARE, LTR, MBS, TCA, TGA
AC199001·2-Contig25 AGO1-1 2e-93 ABRE, ARE, GARE, TGA
AC194028·2-Contig34 Putative tonneau 2 0·0 ARE, EIRE, GARE, TCA
zma-miR171c AC205908·1-Contig87 Scl1 7e-161 ARE, GARE, HSE, LTR, MBS, P-box, TCA
AC202909·2-Contig32 WRKY transcription factor 4e-20 ARE, EIRE, ERE, HSE, MBS
zma-miR319 AC189090·2-contig34 Peptide transporter 3e-122 ARE, HSE, MBS, MRE, TCA
zma-miR399a/b AC209708·1-Contig49 Hypothetical protein 1e-162 ABRE, ARE, GC-motif, TGA
AC212680·1 Contig186 Aminotransferase 2e-26 GARE, HSE, MBS, TCA
AC190908·0-cotig39 Granule-bound starch synthase 0·0 ABRE, ARE, GC-motif, LTR, TGA, plant-AP2
ath-miR395b AC186565·2-Contig10 Beta-d-xylosidase 0·0 ABRE, GC-motif, MBS, plant-AP2
AC199419·3-Contig42 NADP-dependent malic enzyme 0·0 ARE, GC-motif, HSE, LTR, MBS, TGA
AC194854·2-Contig67 ATP sulfurylase 0·0 ABRE, GC-motif, HSE, MBS, SARE
AC206431·1-Contig49 Glycoside hydrolase 5e-88 ABRE, ARE, AuxRR-core, GARE, HSE, MBS, TCA
ath-miR854a AC186510·2-Contig29 Water stress-induced protein 3e-6 ABRE, ARE, GC-motif, MBS, TCA
AC196385·2-Contig31 Dof zinc finger protein 2e-68 ABRE, ARE, GC-motif, MBS
AC194714·3-Contig17 ZmSIG6 2e-168 ARE, C-repeat/DRE, MBS, GC-motif, TGA
ptc-miR474a AZM5_99082 NAD-dependent malic enzyme 2e-143 LTR, MBS, MRE, TCA
AC208836·1 Pumilio/Mpt5 family 2e-69 ERE, GARE, HSE
ptc-miR474b AZM5_12664 Putative protein kinase 0·0 ARE, GC-motif,MRE, TGA
AZM5_102471 Carbonate dehydratase 2e-86 ARE, GC-motif, HSE, LTR, TCA
ptc-miR474c AC199387·3-Contig31 Acyl-CoA thioesterase 3e-151 Unknown
osa-miR396d AC209432·1-Contig40 Growth-regulating factor 2,6 1e-170 Box-W1, HSE,P-box, TC-rich, TCA, Wun
AC190640·3-Contig19 GAMYB 0·0 MBS, TCA
Osa-miR528 AC177830·3-Contig89 Cu,Zn-superoxide dismutase 6e-50 ABRE, AuxRR-core, HSE, TCA, Wun
AC197013·3-Contig16 Hypothetical protein 5e-21 ABRE, GC-motif, LTR, MBS, TGA
AC208577·1-Contig2 bHLH transcription factor 2e-73 ARE, AuxRR-core, GARE, LTR, MBS
AC189099·3-Contig25 Aldehyde dehydrogenase 0·0 ABRE, ERE, GC-motif, plant-AP2

* The mature miRNA sequence was used to maize or rice mRNA database using miRU, a plant microRNA potential target finder (http://bioinfo3.noble.org/miRNA/miRU.htm; Zhang, 2005). If miRNAs did not pair with any hit in miRU, then the miRNA and its reverse complementary sequence were used as a query in the public maize EST database (www.maizesequence.org). The number of mismatches was limited to no more than three nucleotides, insertions or deletions were permitted to consist of no more than one nucleotide, and no more than five G-U pairs were admitted.

About 1500 bp of DNA sequence upstream of the transcription initiation site of each predicted target gene were used to identify cis-acting motifs using PlantCARE (Rombauts et al., 1999; Lescot et al., 2002). ARE, Anaerobic-responsive element; ABRE, ABA-responsive element; AuxRR, auxin-responsive element; ERE, ethylene-responsive element; GARE, gibberellin-responsive element; GC-motif, enhancer-like element involved in anoxic-specific inducibility; HSE, hot-shock element; LTR, low temperature-responsive element; MBS, MYB binding site; TCA/SARE-element, salicylic acid-responsive element; WUN, wound-responsive element.

Key cis-acting element within miRNAs and target genes

Using the PlantCARE motif-finding algorithm, significant matches with sequence motifs in the 5′-upstream of eight miRNA genes were found (Table 4). These cis-acting elements include; the ARE (anaerobic response element), GC-motif, HSE (hot shock element), LTR (low temperature-responsive element), ABRE (ABA-responsive element), GARE (gibberellin-responsive element) and ERE (ethylene-responsive element). Each of these miRNAs has more than one stress-responsive cis-acting element, implicating that these miRNAs are involved in response to various biotic, abiotic and phytohormone stimuli. As shown in Table 4, some of the submergence up-regulated miRNA genes have anaerobic response motifs in their promoters. Especially, seven out of eight miRNAs genes contained ARE and/or GC-motifs, which were found in the 5′-upstream regions of ADH1 (Walker et al., 1987; Dolferus et al., 1994; Hoeren et al.,1998), and specifically in response to anaerobic stress.

Table 4.

Mainly predicted motif in 5′ upstream of microRNA gene

miRNA Accession* Predicted motif in 5′ upstream of microRNA gene
zma-miR159c AC194022·2-Contig40 GARE, MBS, SARE, TCA
zma-miR159d AC189038·2-Contig53 GARE, GC-motif, MBS, TCA
zma-miR160f AC191030·1-Contig73 ARE, TGA
zma-miR166l AZM5_6103 ABRE, ARE,GARE, LTR, MBS, TCA
zma-miR166j AC196406·3-Contig18 ABRE, ARE, GARE, TGA
zma-miR168a AC209687·1-Contig53 ARE, GARE,HSE,LTR,MBS
zma-miR168b AC209687·1-Contig53 ARE,GARE, HSE, LTR, MBS
zma-miR319a AZM5_88200 ARE, GC-motif

* The pre-miRNA sequence was used to query the maize genome sequence (maizesequence.org or maize.tigr.org). The DNA segment flanking queried sequences of not less than 10·0 kb was used to predict the ORF using FGENESH (http://mendel.cs.rhul.ac.uk/).

About 1500 bp DNA sequence upstream of the transcription initiation site of each predicted target gene was used to identify cis-acting motifs using PlantCARE (Rombauts et al., 1999; Lescot et al., 2002). ARE, Anaerobic-responsive element; ABRE, ABA-responsive element; GARE, gibberellin-responsive element; GC-motif, enhancer-like element involved in anoxic specific inducibility; MBS, MYB-binding site; TCA/SARE, salicylic acid-responsive element; HSE, hot-shock element; LTR, low temperature-responsive element.

The 38 predicted target genes also contained various cis-elements involved in response to diverse stimuli. The prevalent cis-elements were: ARE, GC-motif, ABRE, GARE, HSE, LTR and TC-rich repeats (Table 3). The ARE and/or GC-motif was present in the 5′-upstream region of 28 out of 38 targets. In addition, the targets without ARE or GC-motifs had one or more specific cis-elements involved in response to GA or ABA or diverse abiotic stresses. This suggested that the stimuli inducing the target genes as well as the miRNAs at least partially overlap. The miRNAs are involved in the feedback loop control mechanism to attenuate the expression of the target genes.

DISCUSSION

miRNAs respond specifically or non-specifically to submergence stress in maize root cells

Recent studies have shown that ath-miR395 and ath-miR399 were, respectively, up-regulated under low-sulphate and low-phosphate levels in the media (Jones-Rhoades and Bartel, 2004; Fujii et al., 2005). The present microarray data revealed that expressions of ath-miR395b, ppt-miR395 and osa-miR399a were also altered in roots during submergence. Ath-miR395b and ppt-miR395 were down-regulated at the early submergence stage (0–12 h), but were significantly induced after 24 h. Osa-miR399a was dramatically up-regulated at the early stage, and then weakly down-regulated after 24 h, indicating that the three miRNAs may have been regulated by nutrient stress as well as submergence stress. The eight members from the miR159 family across species showed a similar expression profile. They were significantly down-regulated at the 12 h time-point, and recovered to normal levels at the later stage. Because these miRNAs are homologous with four members of zma-miR159 (miR159a/b/c/d), it is suggested that zma-miR159a/b/c/d may be part of the submergence stress response in maize roots.

The miRNAs identified in this study also included a few members of miRNA160, miR166, miR168 and miR171 of maize (Table 2). Sequence analysis of a stress-treated arabidopsis small RNA library indicated that ath-miR393, ath-miR397b and ath-miR402 were up-regulated by ABA, cold, dehydration and salt stress, whereas ath-miR398a was down-regulated (Sunkar and Zhu, 2004; Sunkar et al., 2006). The expression patterns of the four miRNAs, however, did not change in this study, indicating that these miRNAs in maize are not involved in response to submergence stress. Stress-specific regulated miRNAs were also observed in previous studies. The ath-miR319c was specifically up-regulated by cold but not by ABA, dehydration or salt (BH Zhang et al., 2006b). Osa-miR169 g was confirmed as the only member induced by drought in rice (Zhao et al., 2007). The expression profile of osa-miR169 g, however, did not change in cells of submerged maize roots (present study). The differences between miRNAs identified under adverse abiotic stresses with those identified under submerged root cells showed that submergence probably induced a set of specific miRNAs.

The 96 zma-miRNAs on the microarray constituted a very small sample of approx. 500 miRNA genes relative to the >50 000 protein-coding genes in the maize genome (Messing et al., 2004; Fu et al., 2005). In addition, the differentially expressed miRNAs identified in this study constituted only about 6·26 % of the predicted miRNAs. Furthermore, it is known that dramatic metabolic and physiological alterations occurred in maize roots after 12 h of submergence. Metabolic pathways rapidly switched from aerobic metabolism to fermentation (Drew, 1997). In addition, aerenchyma and adventitious roots develop for adaptation to the low-oxygen environment (Kawase, 1981). Amino-cyclopropane carboxylic acid (ACC) synthase, a critical enzyme in ethylene biosynthesis, was also induced (Olson et al., 1995). These metabolic and physiological alterations implicated changes in the global gene expression profiles. If miRNAs are truly involved in the regulation of those alterations, a set of specifically submergence-regulated miRNAs should be expected.

Submergence-responsive miRNAs potentially regulate metabolic and morphological adaptations facilitating survival of maize seedlings under submergence conditions

Plants respond to oxygen limitation with a significant reprogramming of gene expression. Numerous studies have shown that a number of anaerobic polypeptides are induced during low oxygen treatment, while normal APs are dramatically repressed (Sachs et al., 1980, 1996; Chang et al., 2000). Many of the induced proteins were subsequently identified as enzymes of carbohydrate and lipid metabolism, and their accumulation facilitated the supply of energy for normal physiological processes. Interestingly, several mRNAs encoding anaerobic-responsive proteins are also targets of differentially expressed miRNAs. The present microarray data showed that the expression levels of miR162 and miR168 changed as the result of anaerobic induction. The direct targets for these were, respectively, DCL1 and AGO1-1. Both are key proteins during mature miRNA formation in the plant kingdom (Bartel, 2004; Vaucheret et al., 2004). In addition, the accumulation of miR159, ath-miR395-like, ptc-miR474-like and osa-miR528-like were reduced in the early stage of submergence in root cells. Vacuolar-ATPase, ATP sulfurylase, granule bound starch synthase and malic enzyme are important anaerobic proteins. Their mRNAs also are potential targets of miR159, miR399, ath-miR395-like and ptc-miR474-like, respectively (Table 3). The down-regulation of zma-miR159, ath-miR395-like and ptc-miR474-like suggested the occurrence of an accumulation of vacuolar-ATPase, ATP sulfurylase and malic enzyme, while the up-regulation of miR399 could result in a decrease in granule-bound starch synthase and amino-transferase. The down-regulation of ath-miR395-like and ptc-miR474-like resulted in accumulations of sucrose degradation-associated proteins in the cell and enhanced carbohydrate breakdown to supply the substrate for glycolysis to produce ATP. In addition, the accumulation of acyl-CoA thioesterase due to a decrease of ptc-miR474c-like might also ensure a high level of β-oxidation of fatty acids resulting in the release of free coenzyme A and subsequently stored energy.

In addition to energy metabolism, miRNAs might also be involved in other aspects of cellular metabolism. As examples, accumulations of superoxide dismutase and aldehyde dehydrogenase, two targets of osa-miR528-like miRNA, would also aid the elimination of reactive oxygen species and acetaldehyde produced by either a plasma membrane NAD(P)H oxidase and/or mitochondria. This supports the view of a regulated response to oxygen deprivation (Bailey-Serres and Chang, 2005; Agarwal and Grover, 2006).

Accompanied by the metabolic adaptations mentioned above, some miRNAs, including miR166, miR167, miR171, miR399 and osa-miR396-like, were induced in the early phase. It directly altered the level of transcripts encoding TFs such as AGAMOUS and HD-ZIP. Rolled leaf 1 (rld1) of maize is a homologue of the arabidopsis HD-ZIP gene and can be cleaved by miR166 (Juarez et al., 2004). Previous studies showed that miR166-mediated cleavage of HD-ZIP was found to regulate the pattern of vasculature and the establishment or maintenance of abaxial–adaxial polarity in lateral organs (Emery et al., 2003; Kim et al., 2005; Prigge et al., 2005). The accumulation of zma-miR166 under submergence stress indicated that root meristem cell differentiation probably caused the formation of the vascular system with expanded xylem tissue. This hypothesis was confirmed by the induction of ACC synthase and xyloglucan endo-transglycosylase (Olson et al., 1995; Sachs et al., 1996).

Recently, several independent groups of workers have observed that MiR159 regulated key components of auxin signaling pathways and further regulated adventitious root formation and lateral root development (Achard et al., 2004; Mallory et al., 2005; Sorin et al., 2005). It the present study it was found that three ARF transcripts (ARF12, ARF17 and ARF25) and AGO1 in maize were predicted as the targets of zma-miR167 and zma-miR168, respectively. The changes in the expression profiles of both zma-miR167 and zma-miR168 at the early submergence stage can explain the accumulation of ARF transcripts. This event would result in the formation of adventitious roots in the hypocotyl of submerged maize seedlings. It is suggested that this mechanism of morphological adaptation to the anaerobic environment was associated with the regulation of the auxin signal pathway by the miRNA-directed cleavage of ARF mRNA.

Based on the miRNA expression profiles and the functions of miRNA targets, the possible molecular responses and physiological changes that occurred in root cells of maize when submerged have been outlined (Fig. 4). The present study demonstrated the potential role of submergence-responsive miRNAs at the post-transcriptional level in the regulation of the metabolic, physiological and morphological adaptations of maize seedling survival under oxygen-deficient conditions.

Fig. 4.

Fig. 4.

The potential regulating network of submergence-responsive miRNAs in roots cell. The stress-responsive miRNAs could be involved in three pathways to reprogramme complex procedures of metabolism and physiology. (1) Up-regulated miR399 directly targeted cleavage of mRNAs of starch synthase and amino-transferase, prevented metabolic intermediates and glucose from synthesizing starch and amino acid. Accumulated low molecular weight carbohydrate could act as substrate of glycolysis pathway. In addition, the down-regulated miR159, ath-miR395-like and ptc-miR474-like could enhance accumulation of many anaerobic-responsive enzymes involved in carbohydrate and energy metabolism; these accumulated enzymes enhance glycolysis and thus ATP supply. The aerobic metabolism in roots cells would be shifted into anaerobic metabolism during the early submergence phase. (2) Accumulation of SOD and ALDH due to decreasing of osa-miR528-like would aid elimination of reactive oxygen species and acetaldehyde, and thus survival of root cells. (3) The accumulated miR166 and miRNA167 together with down-regulated miR159 could modulate hormone homeostasis via regulating transcripts of HD-ZIP, ARF and GAMYB and then trigger adventitious root formation and lateral root development. The plant has acquired morphological characteristics to adapt to the low-oxygen environment.

ACKNOWLEDGEMENTS

We are grateful to Dr Qiulei Lang (LC-Bio,Hangzhou,China) for technical assistance. We are also grateful to Dr Lifang Zhang (Cold Spring Harbor Laboratory, Cold Spring Harbor, New York) and Dr Bailin Li (Dupont Pioneer USA) for critically revising the manuscript. This work was supported by the Hi-Tech Research and Development Program of China (grant numbers 2008AA10Z112 and 2006AA100103), National Natural Science foundation of China grant numbers 30571171 and 30771352.

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