J. Plant Biol. (2013) 56:187-197

DOI 10.1007/s12374-013-0213-4

The Role of Rice microRNAs in Abiotic Stress Responses

Dong-Hoon Jeong and Pamela J. Green*

Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, Newark, Delaware

19711

Received: May 30, 2013 / Accepted: June 11, 2013

© Korean Society of Plant Biologists 2013

Abstract microRNAs (miRNAs) are a class of small

noncoding RNAs that regulate gene expression at the post-

transcriptional level by mRNA cleavage or translation

inhibition. They play diverse roles in plant growth and

development as well as abiotic stress responses. In response

to abiotic stresses such as drought, salt, cold, heat, and

nutrient limitations, the expression levels of some miRNAs

change, resulting in a modulation of the expression patterns

of miRNA target genes that are associated with stress

adaptations. In rice, stress-responsive miRNAs have been

identified and characterized, and conserved regulation of

conserved miRNAs as well as new regulation by conserved

miRNAs and rice-specific miRNAs is evident. The regulatory

mechanisms controlling target gene expression by stress-

responsive miRNAs include both the coherent and incoherent

regulatory networks that are dynamic and complex. A better

understanding of the regulation of miRNAs and targets during

stress responses can contribute to rice breeding for

improving yield, quality and tolerance to abiotic stresses.

Here, we review current advances in the area of rice

miRNAs and target RNAs associated with abiotic stresses

and discuss how they relate to miRNA-mediated stress-

tolerance.

Keywords: miRNA, Abiotic stress, Target gene, Deep

sequencing, PARE, Rice

Overview of Plant miRNA Biogenesis, Function, and

Identification

MicroRNAs (miRNAs) are 20- to 24-nucleotides (nt) small

non-coding RNAs that repress target gene expression at the

post-transcriptional level (Bartel 2004; Voinnet 2009). They

are encoded by MIRNA genes that are transcribed into the

primary miRNAs (Pri-miRNAs) by RNA polymerase II (Xie

et al. 2005). Pri-miRNAs are processed to become miRNA

precursors (pre-miRNAs), forming self-complementary stem-

loop secondary structures that often have an imperfect

double-stranded character. Mature miRNAs are generated

from this stem-loop structure as a miRNA/miRNA* duplex

by a DICER-LIKE (DCL) protein activity. miRNA strands

of this duplex are then associated with ARGONAUTE

(AGO) proteins in a RNA-induced Silencing Complex (RISC)

while the miRNA*s are rapidly degraded (Park et al. 2002;

Kurihara and Watanabe 2004; Chen 2005).

The regulatory function of plant miRNAs is exerted by

several mechanisms. In general, most plant miRNAs guide

AGO proteins to recognize their target RNAs by near perfect

base-pairing and guide endonucleolytic target RNA

cleavage. Subsequently, target mRNAs are rapidly degraded

by the exosome and an exoribonuclease called XRN4. In

addition, some miRNAs inhibit target mRNA translation,

thereby limiting protein production (Brodersen et al. 2008;

Dugas and Bartel 2008; Lanet et al. 2009; Yu and Wang

2010). miRNAs can also guide cleavage of non-coding

RNAs such as in TAS loci to induce production of trans-

acting siRNAs (Peragine et al. 2004; Vazquez et al. 2004;

Allen et al. 2005) which, in turn, can direct cleavage of

complementary mRNAs. Recently, distinct 22-nt miRNAs

have been reported to facilitate generation of clusters of

phased 21-nt or 24-nt siRNAs (Johnson et al. 2009; Song et

al. 2012). Finally, 24-nt long miRNA, called lmiRNAs, have

been found in rice and direct DNA methylation at their

source and also function in trans on target genes to regulate

gene expression (Wu et al. 2010).

miRNAs have been identified through direct cloning,

sequencing, and analysis of small RNA libraries or through

computational prediction (Jones-Rhoades and Bartel 2004;

Lu et al. 2005). The recent advents of high-throughput

sequencing have greatly increased the rate of identification

of miRNAs. To date, 5,127 pre-miRNAs have been identified

*Corresponding author; Pamela J. Green

Tel : +1-302-831-6160

E-mail : green@dbi.udel.edu

REVIEW ARTICLE

188 J. Plant Biol. (2013) 56:187-197

from 67 plant species and have been registered in the

miRBase sequence Database (release 18.0;Kozomara and

Griffiths-Jones 2011). Of those, 591 pre-miRNAs encoding

708 miRNAs have been reported in rice. They have great

potential to regulate thousands of genes. These observations

emphasize the importance of gene regulatory mechanisms

mediated by miRNAs in addition to those mediated at the

transcriptional level by transcription factors.

Association of Plant miRNAs with Abiotic Stresses

Abiotic stresses, such as drought, salt, cold, heat, and

nutrient deficiency, are major limiting factors in agriculture

and this is certainly the case for rice yield. To adapt and

survive under abiotic stress conditions, sessile plants need an

efficient strategy such as modulation of gene expression.

Proper regulation of stress-responsive genes is important for

both recognition and response to stress conditions. The

ability of plants to employ miRNAs to repress stress-

responsive gene expression post-transcriptionally provides a

considerable advantage compared with regulation by

transcription factors alone. The importance of miRNAs in

abiotic stress responses has been implicated by the fact that

several mutants such as hyponastic leaveas-1 (hyl1), hua

enhancer-1 (hen1), and dcl1, which are defective in miRNA

metabolism, are hypersensitive to the stress hormone

Abscisic acid (ABA) or abiotic stresses in Arabidopsis (Lu

and Fedoroff 2000; Zhang et al. 2008). In addition, the

association of miRNAs with abiotic stress responses has

become clear from the fact that many miRNAs from diverse

species are responsive to abiotic stress (Sunkar and Zhu

2004; Jeong et al. 2011). Induction and/or repression of

miRNAs in response to abiotic stress can modulate the

expression of target genes that may be involved in a

particular stress response and/or tolerance. More importantly,

phenotypic analysis of mutants or transgenic plants, in which

the expression of either stress-responsive miRNAs or their

target genes was manipulated, has proven the role of

miRNAs during the corresponding stress conditions. Below,

we have focused on rice miRNAs that have been implicated

in abiotic stress responses because of the importance of rice

as a major food crop and as a model for other crops.

Drought and Salt Stress-responsive miRNAs in Rice

Drought is the most serious stress to threaten the world’s

food supply. In the case of rice, about half of the land used

for growing rice is affected by drought (Zhang 2007).

Variation in annual rainfall patterns, uneven distribution of

rainfall during the rice growing season, and insufficient

rainfall in many areas contribute to drought stress in rice.

Salt stress is another major agricultural problem effecting

crop yield, especially for rain-fed agriculture in coastal areas

and for irrigated agriculture with poor water quality.

Generally, rice is considered to be relatively more tolerant to

salt stress at germination (Walia et al. 2005). Among cereals,

however, rice is the most salt-sensitive crop at the young

seedling stage (Gongl et al. 2006; Faiyue et al. 2012). Since

both drought and salt stress cause ionic and osmotic stress in

plant cells, these stresses are closely related and share many

common signal transduction mechanisms and gene expression

profiles (Zhu 2002).

In an early study based on microarray experiments,

miR393 and miR169 were identified as up-regulated under

drought stress in rice (Zhao et al. 2007). Reports indicate

miR393 is commonly and consistently up-regulated during

drought stress in many plants such as Arabidopsis,

Medicago, common bean, and rice (Sunkar and Zhu 2004;

Zhao et al. 2007; Arenas-Huertero et al. 2009; Wang et al.

2011). miR393 plays an important role in normal

development, defense against pathogenic bacteria, and the

nitrate response by targeting genes encoding the TIR1

(Transport Inhibitor Response Protein 1)/AFB (Auxin

Signaling F-box Protein) family of F-box auxin receptors

(Navarro et al. 2006; Vidal et al. 2010; Chen et al. 2011). In

rice, miR393 targets two rice auxin receptor gene homologs:

OsTIR1 and OsAFB2, and guides cleavage of their

transcripts (Wu et al. 2009; Li et al. 2010; Zhou et al. 2010;

Xia et al. 2012). Recently, it was reported that over-

expression of miR393 in rice caused them to exhibit

increased tillers and early flowering as well as reduced

tolerance to salt and drought and hyposensitivity to auxin

(Xia et al. 2012). This implies that drought- inducible

miR393-mediated suppression of auxin signaling could

affect the response to drought in plants.

Drought-inducible miR169 was later also reported to be

induced by high salinity in rice (Zhao et al. 2009). However,

a discrepant result was reported in Arabidopsis, in which

miR169 was down-regulated by drought stress treatment (Li

et al. 2008) in contrast to the situation in rice. The down-

regulation of miR169 partially effected drought-induced

expression of its target, NFYA5. Further, the knockout of

nfya5 as well as overexpression of miR169 rendered

Arabidopsis plants more sensitive to drought, whereas NFY5

over-expressing plants exhibited a drought tolerant phenotype

(Li et al. 2008). Further functional analysis of miR169

during drought and salt stress responses in rice may explain

these discrepant results.

Two rice siRNAs, which were previously annotated as

miR441 and miR446 but are currently considered as siRNAs

due to inconsistency with the recent criteria of the

recommended for plant miRNAs (Meyers et al. 2008), were

J. Plant Biol. (2013) 56:187-197 189

reported to be down-regulated by drought stress treatment

(Yan et al. 2011a). They originate from stem-loop precursors

of the miniature inverted-repeat transposable element

(MITE) Stowaway1 and are processed by DCL3a

independent of OsRDR2. Interestingly, while these two

siRNAs, renamed as siR441 and siR446 later, were down-

regulated, their primary transcripts were induced under

drought stress conditions. This implies that processing of

these siRNA precursors was inhibited. Over-expression of

the precursors reduced siR441 and siR446 accumulation and

the corresponding transgenic plants were less sensitive to

ABA and more sensitive to drought stress. It was proposed

that siR441 and siR446 play a positive role in the response

to drought stress by up-regulating MAIF1, which encodes an

F-box protein and is a predicted target of these two siRNAs

(Yan et al. 2011a; Yan et al. 2011b).

miR820 is a rice-specific miRNA and that is down-

regulated by drought stress treatment (Jeong et al. 2011). It

targets OsDRM2, which encodes a DNA methyltransferase

that is involved in RNA-directed de novo DNA methylation

(Pang et al. 2013). Although miR820-mediated OsDRM2

mRNA cleavage was empirically proven (Lu et al. 2008), the

expression of OsDRM2 was also down-regulated when

miR820 decreased during drought stress (Lu et al. 2008;

Jeong et al. 2011). Since the expression levels of a given

miRNA and its target are typically inversely correlated, this

incoherent relationship of their expression patterns implies

that miR820 may fine-tune the spatiotemporal expression of

OsDRM2 in response to drought rather than play a switch

role in its expression. miR820 consists of a 21-nt canonical

miRNA and a 24-nt variant considered to be a long miRNA

(lmiRNAs), which are processed from the same precursor by

DCL1 and DCL3a activities, respectively (Wu et al. 2010).

Canonical 21-nt miR820 is incorporated into the AGO1

protein and regulates OsDRM2 expression primarily through

mRNA cleavage, while 24-nt miR820 is loaded into AGO4

clade proteins and directs DNA methylation of miR820 loci

in cis as well as at OsDRM2 in trans (Wu et al. 2010). Since

DNA methylation by 24-nt miR820 may require OsDRM2

activity, both miR820 and OsDRM2 may cooperate for

negative-feedback regulation of themselves. This implies a

complex regulatory network, including incoherent regulation,

negative feedback, and antagonistic activities.

miRNAs Responsive to Temperature Stress in Rice

Extreme temperatures, such as cold or heat, affect not only

the growth duration, but also the growth pattern and

productivity of rice crops. The critical temperatures for the

development of the rice plant at different growth stages

varies (Nguyen 2002). For example, cold stress has a higher

impact at the germination and reproductive anthesis stages

compared to the vegetative growth stages. High temperature

stress more seriously affects the reproductive anthesis and

seed ripening stages, resulting in damage to grain fertility.

Cold-stress-responsive rice miRNAs have been reported

based on genome-wide profiles of miRNA expression

determined using microarray or deep sequencing methods

(Jian et al. 2010; Lv et al. 2010; Jeong et al. 2011). Of these,

miR167 and miR319 were shown to be down-regulated by

cold stress in rice seedlings (Lv et al. 2010). While their

precursors are down-regulated after 3-h, the mature miRNAs

are decreased after 12h of cold stress. Among the predicted

targets of miR319, two genes that encode TEOSINTE

BRANCHED1, CYCLOIDEA, and PCF (TCP) transcription

factors and one gene that encodes a MYB transcription

factor were up-regulated after cold treatment. Intriguingly,

both miR167 and miR319 were reported to be up-regulated

by the cold stress in Arabidopsis (Sunkar and Zhu 2004;

Zhou et al. 2008). This is another example of a discrepancy

between the miRNA expression patterns between

Arabidopsis and rice. Such differences may be due to

variations in either experimental conditions or the methods

used to measure miRNA expression changes. However, it is

also possible that these miRNAs play a species-specific role

in cold responses.

Deep sequencing data and the following validation

experiment showed that the expression of miR1425 was

suppressed during cold stress in rice panicle tissues.

miR1425 targets a set of genes encoding Pentatricopeptide

repeat (PPR) proteins that are RNA-binding proteins involved

in post-transcriptional processes such as RNA splicing, RNA

editing, RNA stability and translation in organelles such as

mitochondria and chloroplasts (Delannoy et al. 2007; Schmitz-

Linneweber and Small 2008). A group of PPR genes are

known to be targeted by multiple miRNA families such as

miR161 and miR400, or by TAS1 and TAS2 trans-acting

siRNAs that are generated after cleavage of the TAS transcripts

is mediated by miR173 in Arabidopsis (Rhoades et al. 2002;

Sunkar and Zhu 2004; Allen et al. 2005). miR1425 is a rice-

specific miRNA that targets PPR genes (Lu et al. 2008).

Fertility restorer (Rf-1) gene, which encodes a PPR protein

and that is a target of miR1425, is known to lead to increased

cold tolerance in hybrid rice at the booting stage by increasing

the number of potentially fertile pollen grains (Komori and

Imaseki 2005). Rf-1 was up-regulated during cold stress when

miR1425 is down-regulated, implying that miR1425 plays

role in modulating the expression of Rf-1 under cold

conditions (Jeong et al. 2011).

miR812q was reported to be extremely up-regulated by

cold stress at the booting stage of rice plants (Jeong et al.

2011). It is a 24-nt miRNA that originates from a stem-loop

precursor of MITE Stowaway1. The MIR812 family is

190 J. Plant Biol. (2013) 56:187-197

comprised of 17 precursors that share sequence similarities.

However, miR812q is generated from a sequence-diverged

region and has a unique miRNA sequence compared to the

other family members. In addition, miR812q is unique

among family members because it responds to cold stress,

suggesting miR812q is a new evolving miRNA in rice.

Calcineurin B-like (CBL) protein interacting protein kinase

10 (CIPK10) is targeted for cleavage by cold-inducible

miR812q, and thus down-regulated during the cold stress

(Jeong et al. 2011). CIPK genes are regulated by various

abiotic stresses and mediate environmental stress tolerance in

the Ca2+-dependent CBL-CIPK signaling pathway (Xiang et

al. 2007; Batistic and Kudla 2009).

High-temperature-responsive miRNAs have not been

studied well in plants in comparison to other stress-

responsive miRNAs, and have only been reported in

Populus, Brassica rapa, wheat, and rice (Lu et al. 2008; Xin

et al. 2010; Jeong et al. 2011; Yu et al. 2012). In rice,

miR397b.2 is induced by heat stress. Previously, miR397 in

Arabidopsis was reported to be up-regulated by salt stress

treatment (Sunkar and Zhu 2004) but, the expression of rice

miR397 was not changed by cold stress. Intriguingly, a target

of miR397b.2, which encodes an L-ascorbate oxidase, is

down-regulated during the heat stress while miR397b.2 is

increased, and is induced by salt stress in rice (Jeong et al.

2011). This indicates that the rice miR397 family has

evolved to modulate the expression of L-ascorbate oxidase

under heat stress rather than salt stress.

miRNAs Associated with Nutrient Homeostasis in Rice

Macronutrients, such as phosphorus, sulfur, nitrogen, and

potassium, are essential and required for normal growth and

development of plants. They are so limited in soil that their

acquisition, assimilation, and metabolism are tightly regulated

in plants. Deprivation of specific macronutrients commonly

affects the quality and production of crop plants such as rice.

Recent studies have implicated the involvement of miRNAs

in nutrient homeostasis.

The association of the phosphorus-deprivation response

with miRNAs is well studied for miR399 and miR827. The

expression of both miRNAs is specifically induced when the

plants are deprived of phosphate (Pi) which is the naturally

occurring form of phosphorus. Up-regulation of miR399 is

well-conserved in many plants such as Arabidopsis, tomato,

common bean, and rice (Fujii et al. 2005; Aung et al. 2006;

Bari et al. 2006; Chiou et al. 2006; Valdés-López et al.

2008). PHR1, a MYB transcription factor, is known to

induce the expression of miR399 in response to Pi starvation

in Arabidopsis (Fujii et al. 2005). In rice, OsPHR2, the

homolog of AtPHR1, is implicated as a significant regulator

of miR399 expression under Pi starvation conditions (Zhou

et al. 2008) . Up-regulation of miR399 results in down-

regulation of its target, PHO2 which encodes ubiquitin-

conjugating E2 enzyme (UBC24). PHO2 negatively

regulates Pi uptake and translocation by degrading target

proteins such as PHO1 which has been implicated in Pi

loading to xylem (Liu et al. 2012). Thus, miR399-mediated

PHO2 down-regulation under Pi starvation conditions

facilitates Pi uptake and translocation. Over-expression of

miR399 in Arabidopsis induces more accumulation of Pi

than wild type, and transgenic plants expressing a PHO2

mRNA engineered to be insensitive to miR399 showed less

inhibition of primary root growth during Pi deprivation than

those of wild type plants (Fujii et al. 2005; Aung et al. 2006).

In rice, a PHO2 ortholog was identified by map-based

cloning of the leaf tip necrosis1 (ltn1) mutant (Hu et al.

2011). The ltn1 mutant exhibited increased Pi uptake and

translocation even under Pi-sufficient conditions. The

resulting excessive Pi accumulation leads to toxicity and

causes growth defects and leaf tip necrosis. Transgenic rice

plants constitutively over-expressing Osa-MiR399 displayed

a phenotype similar to that of the ltn1 mutant and exhibited

down-regulation of LTN1 transcripts. This suggests the role

of the rice miR399-LTN1 module in the Pi signaling is

similar to that of Arabidopsis miR399-PHO2 (Hu et al.

2011).

Interestingly, the activity of miR399 is known to be

regulated by the TPSI1/Mt4 gene family of noncoding

RNAs. In Arabidopsis, the At4/IPS1 (INDUCED BY

PHOSPHATE STARVATION1) gene in this family functions

to encode target mimics that modulates the activity of

miR399 by sequestering it from binding to PHO2 mRNA

(Franco-Zorrilla et al. 2007). In this model, both At4 and

miR399 are up-regulated under Pi starvation conditions

(Shin et al. 2006). Thus, PHO2 expression is maintained

under Pi starvation despite the presence of an abundant level

of miR399 (Aung et al. 2006; Bari et al. 2006). Since

homologs of At4/IPS1 genes are present in many plant

species (Rymarquis et al. 2008), target mimicry-based

regulation of miR399 could be a conserved mechanism. In

rice, At4 homolog, OSPI1 (Oryza sativa phosphate-

limitation inducible gene 1) was identified and up-regulated

during the Pi starvation (Wasaki et al. 2003).

In addition to miR399, miR827 was also identified as a

well-conserved and Pi-starvation inducible miRNA both in

Arabidopsis (Hsieh et al. 2009; Pant et al. 2009) and rice

(Lin et al. 2010; Jeong et al. 2011) . In Arabidopsis, it targets

the NLA (Nitrogen Limitation Adaptation) gene which

encodes a RING-type ubiquitin ligase with an SPX (SYG1/

Pho81/XPR1) domain involved in the response to nitrogen

deficiency (Peng et al. 2007). This implies that miR827 may

play role in the cross talk between the signaling pathways

J. Plant Biol. (2013) 56:187-197 191

responding to Pi limitation and nitrogen limitation. Indeed,

NLA was recently reported to participate in the regulation of

Pi homeostasis in a nitrate-dependent manner by regulating

the expression of a high-affinity phosphate transporter

PHT1.1 and its traffic facilitator PHF1 (Kant et al. 2011).

Instead of targeting OsNLA, rice miR827 targets two distinct

genes: OsSPX-MFS1 and OsSPX-MFS2, which encode

proteins with SPX and MFS (Major Facilitator Superfamily)

domains. Although both genes are negatively regulated by

miR827-mediated mRNA cleavage events, they show

opposite expression patterns in response to Pi starvation. The

expression of OsSPX-MFS1 is reduced upon Pi starvation,

indicating that a direct relationship between induction of

miR399 and down-regulation of OsSPX-MFS1.In contrast,

the expression of OsSPX-MFS2 is increased during Pi

starvation, suggesting the involvement of complex regulation

of miR827 and its target genes in rice. Both a TOS17

transposon insertion mutant of OsSPX-MFS1( mfs1) and a

transgenic plant over-expressing miR827 showed impaired

Pi homeostasis and over-accumulated Pi (Wang et al. 2012).

During the limitation of sulfate, which is a major source of

sulfur, the expression of miR395 is significantly up-regulated

in Arabidopsis (Jones-Rhoades and Bartel 2004) and rice

(Jeong et al. 2011). In both plants, miR395 targets two

families of genes, ATP sulfurylase (APS) and Sulfate transporter

(SULTR), which are involved in sulfate accumulation and

allocation, respectively. In Arabidopsis, the abundance of

APS1 transcripts decreases when miR395 increases during

sulfate starvation which is the expected negative correlation

between miRNA and its target (Jones-Rhoades and Bartel

2004). However, another target, SULTR2;1, is up-regulated

during sulfate starvation when miR395 is up-regulated.

These discrepant expression patterns might be explained by

their precise spatial expression patterns. miR395 is mainly

expressed in phloem companion cells (Kawashima et al.

2009) while SULTR2;1 is mainly expressed in xylem

parenchyma cells (Takahashi et al. 1997; Takahashi et al.

2000). Thus, it is proposed that the function of miR395 is to

suppress SULTR2;1 expression in phloem companion cells

under conditions of sulfate limitation to restrict SULTR2;1

expression to the xylem. Similar results were also observed

in rice (Jeong et al. 2011). During sulfate starvation, one

miR395 target, SULTR1, is down-regulated, whereas the

other targets, SULTR2 and APS1, are up-regulated when

miR395 is induced. The precise spatial expression patterns of

these targets have yet to be determined in rice. Thus, more

experiments are needed to clarify the role of miR395 in rice

during sulfate starvation.

The association of miRNAs and nitrogen signaling has

been well studied within the context of auxin-mediated

lateral root growth in Arabidopsis. Under nitrogen limiting

conditions, miR167 is specifically down-regulated while its

target, Auxin responsive factor 8 (ARF8), increases, resulting

in lateral root initiation (Gifford et al. 2008). In addition, the

miR399/AFB3 target RNA module was also reported to play

a role in nitrogen-auxin crosstalk involved lateral growth

development in Arabidopsis (Vidal et al. 2010). Nitrate

treatment induces both miR393 and its target, AFB3 which

encodes an auxin receptor. This incoherent feed-forward

mechanism affects primary and lateral root growth responses

to nitrate. Whether miR167/ARF8 and miR393/AFB3

regulatory modules also play a role in nitrogen signaling in

rice has not yet been reported.

Comprehensive expression profiles of miRNAs have

revealed many nitrogen starvation-responsive miRNAs in

Arabidopsis (Pant et al. 2009; Liang et al. 2012), rapeseed

(Pant et al. 2009), maize (Zhao et al. 2012), and rice (Jeong

et al. 2011; Nischal et al. 2012). Among these, miR169 is

usually reported to be down-regulated under conditions of

nitrogen limitation in Arabidopsis, maize, and rice. Further

study in Arabidopsis revealed that target genes of miR169,

specifically, the NFYA family transcription factors, were

induced during nitrogen starvation when miR169 is repressed

(Pant et al. 2009). Moreover, transgenic Arabidopsis plants

over-expressing MIR169a accumulated less nitrogen and

were more sensitive to nitrogen stress than the wild type

(Zhao et al. 2011). It is notable that miR169 and the NFYA

genes were also reported to be involved in drought stress

responses (Li et al. 2008), implying that low expression of

miR169 during nitrogen limitation could contribute to

drought tolerance of N-limited plants.

Rice-specific miR3979 was reported to be down-regulated

under nitrogen starvation conditions (Jeong et al. 2011). It is

intriguing that miR3979 is a root–preferential miRNA and

consequently, its regulation in response to nitrogen supply is

limited only to roots, where nitrogen is mainly absorbed.

miR3979 is predicted to target a gene encoding an anthranilate

phosphoribosyl-transferase which is involved in tryptophan

(Trp) biosynthesis. It is known that the Trp biosynthetic pathway

in plants leads to the production of not only Trp but also

secondary metabolites such as the phytohormone auxin and the

phytoalexin camalexin (Kutchan 1995; Radwanski and Last

1995). Trp biosynthetic genes are generally induced by amino

acid starvation as well as abiotic and biotic stresses (Zhao et al.

1998). Thus, it is possible that, during nitrogen limitation, down-

regulation of miR3979 induces Trp biosynthesis followed by

increased auxin and camalexin, resulting in lateral root initiation

and stress resistance, respectively.

Mechanisms of Target Gene Regulation by Stress-

Responsive miRNAs

Efforts to profile rice miRNAs have identified many

192 J. Plant Biol. (2013) 56:187-197

stress-responsive miRNAs which are either induced or

repressed during abiotic stress. Given that miRNAs negatively

regulate the expression of their target genes by target RNA

cleavage or translation repression (Voinnet 2009; Huntzinger

and Izaurralde 2011), the expression patterns of miRNA

target genes generally show an inverse correlation with those

of miRNAs. Therefore, for the majority of cases that involve

target cleavage, the simple expectation is that, when

miRNAs are induced by stress treatments, their target

mRNAs are reduced and vice versa (Fig. 1A). Furthermore,

this negative correlation between target mRNA and miRNA

accumulation is often considered proof of miRNA targeting.

Indeed, in many cases, the expression of the stress-regulated

miRNA and its targets are mutually exclusive, such as an

example observed in miR399 and its target PHO2 suggesting

that the stress-responsive miRNA is responsible for

switching off the expression of target genes under stress

conditions. However, many other cases also represent an

opposite trend such that miRNAs and their targets are co-

expressed in the same tissue or under the same stress

conditions. One striking, well-characterized example is the

case of miR168 targeting of AGO1 in Arabidopsis. The

miRNA is expressed everywhere in the plant where its target

is required, thus implying the involvement of fine tuning

mechanisms to modulate gene expression through a miRNA-

mediated feedback loop (Vaucheret et al. 2004; Vaucheret et

al. 2006). Another example of co-expression of a miRNA

and its target was observed for miR395 and SULT2;1 where

both are up-regulated in response to sulfate starvation. As

mentioned earlier, the differential expression patterns of

miR395 and its target SULT2;1 in a cell-type specific

manner gave a clue to explain the discrepancy of their

expression. A general illustration of such spatial regulation is

shown in Fig. 1B. A miRNA that is highly expressed in a

cell type restricts the expression of its target where it is

expressed. Conversely, the target gene is specifically

expressed in a cell type in which the miRNA is lowly

expressed. In this situation, examination of the stress-

responsive expression patterns in whole organs would

obscure the complex and subtle changes that could be

detected with cell type-level resolution (Dinneny et al. 2008;

Iyer-Pascuzzi et al. 2011).

The relationship of expression patterns between a miRNA

and its target RNAs is more dynamic and complex in a

regulatory network where transcriptional induction/

repression by transcription factors and post-transcriptional

repression by miRNAs co-exist. Under a stress-condition,

transcription of both stress-responsive miRNAs and their

target genes can be independently regulated. Their regulation

can be either in the same or the opposite direction. In other

words, transcriptional regulation of a miRNA and its target,

during a stress, can be induction/repression (Fig. 2A),

repression-induction (Fig. 2B), induction of both (Fig. 2C),

or repression of both (Fig. 2D). The first two examples are

in a coherent network where the effects of transcriptional and

posttranscriptional regulatory pathways on miRNA-target

gene expression are the same (Fig. 2A and B). The other two

examples show in an incoherent network where two

pathways have opposite effects (Fig. 2C and D). In coherent

regulation, miRNAs play cooperative switch-like roles along

with transcription factors. For example, under stress, both the

miRNA and the transcriptional repressor suppress target

gene expression. Thus, these two regulatory pathways

cooperate to repress the target gene rapidly (Fig. 2A). In the

other example of coherent regulation, target gene expression

is rapidly increased by the combination of miRNA

repression and the function of a transcriptional activator (Fig.

2B). In this case, another role of the miRNA is to repress

target gene expression under normal conditions, minimizing

the basal level of target expression. In the case of incoherent

regulation, miRNAs function to fine-tune target gene

expression rather than switch it on and off. For instance,

under a given stress condition, both a transcriptional

activator and a miRNA may be induced (Fig. 2C) as was

observed in Arabidopsis miR393/AFB3 under conditions of

Fig. 1. Spatiotemporal effects of stress-regulated miRNAs ontarget gene expression. A. Temporal regulation of target geneexpression by stress-regulated miRNAs. Stress-induced miRNAsdown-regulate the expression of their target genes during a givenstress condition, while stress-repressed miRNAs up-regulateexpression of their target genes during the stress condition. B.Spatial regulation of target gene expression by stress-regulatedmiRNAs. Stress-responsive miRNAs that are regulated in a cell-type-specific manner can spatially restrict the expression of theirtargets in a particular cell or cell type.

J. Plant Biol. (2013) 56:187-197 193

nitrogen limitation. In this situation mentioned earlier, up-

regulation of AFB3 is modulated by miR393 induction in an

incoherent negative feed-forward loop. Stress-inducible

target gene expression patterns may take the form of a

saturated curve or a pulse depending on the strength of

miRNA repression. The other example of incoherent

regulation was observed in the rice miR820/OsDRM2

module where both the miRNA and the target gene were

repressed by drought stress (Fig. 2D). In this case, the

fundamental role of the miRNA is to keep the expression of

the target gene at basal levels under normal conditions.

However, as drought stress down-regulates the expression of

OsDRM2 at the transcriptional level, and the miR820-

mediated repressive pathway is transcriptionally dampened,

slow repression of target gene expression ensues. Taken

together, these scenarios illustrate that miRNA functions can

be fully understood only by addressing regulatory interactions

within networks.

Conclusions and Future Prospects

In this review, we have discussed our current understanding

of the role of rice miRNAs in response to abiotic stresses

including drought, salt, cold, high temperature, and the

limitation of nutrients such as Pi and sulfate. In particular, we

have provided the evidence that stress-regulated rice

miRNAs play a role in modulating expression levels of their

target genes which are involved in stress responses and

adaptation. Although the stress responsiveness of some rice

miRNAs is well conserved in other plants, new regulation of

conserved miRNAs as well as stress regulation of rice-

specific miRNAs was also reported, highlighting the

potential for identification of more stress-responsive

miRNAs in rice. Moreover, we highlighted the diverse

regulatory mechanisms and patterns of target gene

expression by stress-responsive miRNAs. In addition to

coherent regulation by miRNAs, incoherent relationships

between miRNAs and their target gene expression levels

provide another layer of gene regulatory networks in a stress-

responsive pathway.

Despite many reports introduced in this review, there are

still limitations to our understanding on the role of rice

miRNAs in abiotic stress responses. First, many regulated

miRNA candidates that were originally identified by high-

throughput analysis using microarrays or deep sequencing

lack validation experiments to confirm their expression

patterns. It has been reported that a technical bias, introduced

by hybridization, ligation efficiency, PCR amplification, or

sequencing methods, often leads to results being inaccurate

(Zhang et al. 2011). Thus, each individual miRNA

expression pattern during the stress conditions must be

carefully examined by another validation assay such an RNA

blot, a quantitative RT-PCR, or the splinted-ligation mediated

miRNA detection method, before follow up studies. While

the first two experiments are widely used for quantification,

the splinted-ligation mediated detection method is primarily

proposed to discriminate among miRNA variants including

members of miRNA families and isomiRs (Jeong and Green

2012). Second, detailed information about spatial and

temporal expression patterns of stress-regulated miRNAs

Fig. 2. The effects of stress-responsive miRNAs and transcriptionalregulators on expression of target RNA. Stress-inducible orrepressible miRNAs cooperate with transcriptional regulators tocontrol the expression pattern of miRNA-target genes during stressconditions. The expression patterns of miRNAs and their targetscan be either coherent or incoherent as illustrated in the followingexamples. A. Coherent repression of a target expression by astress-inducible miRNA and a transcriptional repressor. B.Coherent induction of a target expression by a stress-repressiblemiRNAs and a transcriptional activator. C. Incoherent induction ofa target gene by a stress-inducible miRNA and a transcriptionalactivator. D. Incoherent repression of a target gene by a stress-repressible miRNA and a transcriptional repressor. Circled A,Activator; circled R, Repressor.

194 J. Plant Biol. (2013) 56:187-197

and their targets are often lacking in rice. Most reported

studies have analyzed expression profiles in whole plants

subjected to a specific stress at a single time point and most

cases were done during the early seedling stage. Given that

differential regulation of genes in different tissues is

important for response to stress, dynamic data including

various tissues and time points can provide valuable

information to better understand the underlying stress

responses that might be missed by using data that only

focuses on whole organs at a single time point. Moreover,

systemic analysis of relationships between expression

patterns of miRNAs and their target genes during time

courses and from diverse tissues or cell types could provide

better understanding of gene regulatory network in stress

response pathways. The third limitation to our knowledge of

the role of stress-responsive rice miRNAs is the

identification of authentic target RNAs. Although the is

general consensus that the relevance of regulated miRNAs in

stress responses will be mainly defined by their activity on

target mRNAs, the exploration of rice miRNA targets has

mainly relied on their computational prediction. Mapping the

miRNA-mediated cleavage site on a target mRNA is the

most direct empirical evidence for plant miRNA target

identification. The analysis of Parallel Analysis of RNA

Ends (PARE), also called degradome analysis, has been

proposed for genome-wide identification of miRNA targets

(Addo-Quaye et al. 2008; German et al. 2008; Gregory et al.

2008). PARE was reported in rice to be successful in

identifying and characterizing many rice miRNA targets

from tissues that were grown under healthy conditions (Wu

et al. 2009; Li et al. 2010; Zhou et al. 2010; Jeong and Green

2012). The next challenge will be to analyze PARE data

from the stress-treated tissues for a better understanding of

stress-regulated miRNA-mediated target gene regulation.

Finally, we would like to point out the current large gap

between the identification of stress-regulated miRNAs and

the confirmation of their function. The fact that a miRNA is

differentially regulated in response to an environmental

stress does not necessarily mean that the miRNA is involved

in stress responses. Thus, the use of transgenic or mutant

approaches is essential to better understand the biological

function of miRNAs. Due to the redundancy of members of

miRNA families and the relatively small size of MIR genes,

it is generally difficult to obtain insertional knockout mutants

of stress-responsive miRNAs. Thus, the miRNA-overexpressing

transgenic plants are commonly used for studying miRNA

functions. In addition, gain-of-function mutants, in which

miRNA-resistant target genes are ectopically expressed, can

demonstrate functions of the miRNA that phenotype occurs

when miRNA-mediated regulation is blocked. Moreover, it

was recently proposed that transgenic plants overexpressing

an artificial target mimic transcript can provide insight into

miRNA function by sequestering miRNAs of interest

(Todesco et al. 2010; Yan et al. 2012).

Abiotic stress tolerance is a complex trait that is one of the

important quantitative traits for rice breeding. To improve

this trait, most QTL studies have focused on the isolation of

protein coding genes that are responsible. It is now clear that

we also need to consider post-transcriptional regulation by

noncoding RNAs such as miRNAs. In Arabidopsis, a

naturally occurring single nucleotide polymorphism in the

MIR164A gene alters the efficiency of miRNA processing,

affecting leaf shape and shoot architecture in Arabidopsis

(Todesco et al. 2012). In rice, a single nucleotide

polymorphism in the miR156 and miR529 target site of

OsSPL14 elevates expression of the target resulting in fewer

tillers, more panicle branching, and higher yields in rice (Jiao

et al. 2010; Miura et al. 2010; Jeong et al. 2011). These

findings emphasize that stress-regulated miRNAs and

miRNA target sites need to be seriously considered during

QTL analysis to maximize future crop improvement efforts.

Acknowledgments

We thank Bryan von Hagel for editorial assistance. Our work in thisarea was primarily supported by the Agriculture and Food ResearchInitiative Competitive Grants Program grant no. 2011-67013-30036from the USDA National Institute of Food and Agriculture (NIFA),with additional support from USDA-NIFA grant # 2007-35100-18268 and DOE grant # DE-FG02-07ER64450.

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