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Contents lists available at ScienceDirect

Journal of Plant Physiology

0176-16

doi:10.1

Abbre

factor; C

sequenc

Hyl1, hy

sequenc

transcri

trans-ac

PCF (TC

whole-gn Corr

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PleasPlant

journal homepage: www.elsevier.de/jplph

Identification of microRNAs and their targets in switchgrass,a model biofuel plant species

Jessica Matts a, Guru Jagadeeswaran a, Bruce A. Roe b, Ramanjulu Sunkar a,n

a Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK 74078, USAb Department of Chemistry and Biochemistry, University of Oklahoma, 101 David L. Boren Blvd., Norman, OK 73019, USA

a r t i c l e i n f o

Article history:

Received 8 January 2010

Received in revised form

4 February 2010

Accepted 5 February 2010

Keywords:

microRNAs

miRNA targets

Nutrient deprivation

Post-transcriptional gene regulation

Switchgrass

17/$ - see front matter & 2010 Elsevier Gmb

016/j.jplph.2010.02.001

viations: AP2-like, apetala 2-like transcription

BP, cap-binding protein; DCL4, dicer like-4;

es; HEN1, Hua enhancer-1; HTGS, high-throu

ponastic leaves-1; miRNAs, miroRNAs; NR, n

es; RACE, rapid amplification of cDNA ends;

ption factors; SPL, squamosa promoter bindin

ting small interfering RNAs; TCP factors, teos

P)-domain protein family; TIR1, transport inh

enome shotgun reads

esponding author. Tel.: +1 405 744 8496; fax

ail address: ramanjulu.sunkar@okstate.edu (R

e cite this article as: Matts J, et al. IPhysiol (2010), doi:10.1016/j.jplph

a b s t r a c t

In recent years, several plant species such as switchgrass, Miscanthus and Brachypodium have been

recognized as potential model plant species for cellulosic bioenergy production. Of these, switchgrass

has attracted much attention in the United States and worldwide because it can grow well on marginal

lands and tolerate frequent drought spells. However, little is known about the basic biology of the traits

that control these important characteristics in switchgrass. Genome-encoded �21–24 nt microRNAs

(miRNAs) have emerged as critical regulators of gene expression important for normal growth and

development and adaptation to abiotic stress, including nutrient-deprived conditions. To understand

miRNA-guided post-transcriptional gene regulatory networks in this plant species, we sought

to identify miRNAs in switchgrass. Using computational and experimental approaches, we identified

�20 conserved miRNA families. Temporal expression analysis indicated that some miRNAs have

distinct tissue-specific expression, although most are ubiquitously expressed. Unlike in Arabidopsis and

other plants, miR395 and miR399 were detected in plants grown on optimal levels of sulfate or

phosphate in switchgrass, and were only slightly altered when exposed to sulfate or phosphate deficit

conditions. Thirty-seven genes were predicted as targets for miRNAs, and 4 target mRNAs (Squamosa

promoter binding-like factor, apetala 2-like, NAC domain containing transcription factor and HD-Zip

homologs) were validated by 50-RACE assays. These findings provide a snapshot of the miRNA

component and possible targets in switchgrass.

& 2010 Elsevier GmbH. All rights reserved.

Introduction

Post-transcriptional gene regulation mediated by endogenoussmall non-coding RNAs such as microRNAs (miRNAs) andtrans-acting small interfering RNAs (tasiRNAs) play a criticalrole in diverse aspects of plant development, including auxinsignaling, meristem boundary formation and organ separation,leaf development and polarity, lateral root formation, transitionfrom juvenile to adult vegetative phase and from vegetative toflowering phase, floral organ identity and reproduction, as well asadaptation to biotic and abiotic stresses, including nutrientdeprivation (Jagadeeswaran et al., 2009a; Jones-Rhoades et al.,

H. All rights reserved.

factor; ARF, auxin response

GSS, genomic survey

ghput genomic sequences;

on-redundant nucleotide

SCL, scarecrow-like

g protein-like; tasiRNAs,

inte branched 1, cycloidea,

ibitor response 1; WGS,

: 1 405 744 7799.

. Sunkar).

dentification of microRNAs.2010.02.001

2006; Mallory and Vaucheret, 2006; Shukla et al., 2008; Sunkarand Zhu, 2004; Sunkar et al., 2007). Mature miRNAs (21-nt)are generated from longer RNA hairpin precursors by theendoribonuclease III-like enzyme, dicer like-1 (DCL1). Hyponasticleaf-1 (a dsRNA binding protein), serrate (a C2H2 zinc fingerprotein), 2 cap-binding proteins (CBP20 and CBP80) and HEN1(a methyltransferase) are also essential for miRNA biogenesis andaccumulation in plants (Dong et al., 2008; Kim et al., 2008;Laubinger et al., 2008; Liu et al., 2005; Ramachandran andChen, 2008; Yang et al., 2006). Mutations in all these proteinscause reduced miRNA levels and increased pre-miRNA levels,as well as increased accumulation of miRNA target transcripts.The processed and methylated miRNA/miRNAn duplex isexported to the cytosol via HASTY5, a plant ortholog of exportin(Park et al., 2005). miRNAs that are incorporated into anargonaute containing RNA-induced silencing complex can affectthe target gene expression. miRNA- and tasiRNA-mediatedregulations rely on specific miRNA target mRNA interactionsthat result in degradation of the target transcript and/orattenuation of translation (Bartel, 2009; Jones-Rhoades et al.,2006; Voinnet, 2009).

The stable and continuous flow of future biofuels will require aconstant supply of biomass grown specifically for biofuel

and their targets in switchgrass, a model biofuel plant species. J

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production. Unlike corn, switchgrass is not part of the human diet,so it is a more reliable source for biofuel production. Switchgrassis a perennial, rhizomatous (with nodes) grass and is native to theprairies of North America (Bouton, 2007). Besides its use as aforage crop, switchgrass has emerged as an ideal candidate forbiofuel production because it: (1) grows very tall (3–10 feet tall,depending on the ecotype/cultivar); (2) thrives well in marginaland waste lands, requiring little input (fertilizer); (3) thrivesunder drought conditions, and (4) is considered a carbon sinkbecause of its large root system (Clark, 2002; Keshwani andCheng, 2009; Schmer et al., 2008). Despite the increase inimportance of switchgrass as an energy crop, little is knownabout the basic biology of the traits that make it a useful crop.Identification of the gene regulatory processes contributing tobiomass accumulation, nutrient uptake and assimilation, andstress resistance could help in the design of rational strategies forimproving switchgrass, as well as other biofuel-related speciessuch as Brachypodium and Miscanthus.

One of the primary objectives in bioenergy production is toimprove the biomass accumulation of a biofuel plant species.Recent functional studies of specific miRNAs in Arabidopsis, riceand maize demonstrated that manipulation of specific miRNAscan improve biomass accumulation in transgenic plants. Forinstance, miR156 overexpression in Arabidopsis led to a moderatedelay in flowering, severe decrease in apical dominance andprolonged vegetative phase (Schwab et al., 2005). The combina-tion of these traits led to a 10-fold higher total leaf number intransgenic plants than in wild-type plants (Schwab et al., 2005). Inrice and maize, miR156 overexpression led to increased tillernumber and prolonged vegetative phase, which resulted inenhanced biomass accumulation (Chuck et al., 2007; Xie et al.,2006). These findings imply a role for miRNAs in the regulationof important plant characteristics that improve biomassaccumulation.

Because miRNAs are involved in a wide variety of biologicalprocesses, their identification in diverse plant species is important(Sunkar and Jagadeeswaran, 2008; Zhang et al., 2006). To obtainbetter insight into the biological function of miRNAs in generaland individual miRNAs in particular, identifying all miRNAs thatare expressed in a plant species is essential. In recent years,several plant species including Brachypodium (Unver and Budak,2009; Zhang et al., 2009) have been analyzed for their miRNAcomponent. However, miRNAs have not been identified inswitchgrass, an important model biofuel plant species. Here wereport on the identification and characterization of miRNAs, theirexpression patterns and mRNA targets in switchgrass.

Materials and methods

Computational approach for identification of conserved miRNAs in

switchgrass

Computational approaches have been successful in theidentification of conserved miRNAs in diverse plants (Sunkarand Jagadeeswaran, 2008; Unver et al., 2009; Zhang et al., 2006).The basis for computational identification is the conservedmature miRNA sequence coupled with the predictable secondarystructure for its primary miRNA transcript (Ambros et al., 2003;Sunkar and Jagadeeswaran, 2008; Zhang et al., 2006).

Parameters for BLASTN searches and secondary structure predictions

Conserved miRNAs are highly identical in sequence and mayvary by 1 to 2 nt among diverse plant species. We used the mature

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

miRNA sequences obtained from Arabidopsis (miRBase) as aquery in BLAST searches against NCBI’s EST database. Foridentification of monocot-specific miRNAs, miRNA sequencesfrom rice were used. We used NCBI BLASTN to find homologousmiRNA sequences for switchgrass that matched at least 18 nt andleft 3 nt for possible sequence variations. Hits among the ESTswith these criteria were considered candidates for conservedmiRNAs. The flanking region of the mature miRNA sequence wasextracted and used for fold-back structure predictions with use ofmFOLD (http://mfold.bioinfo.rpi.edu/cgi-bin/rna-form1.cgi). Theobtained secondary structures were compared with secondarystructures deposited in the miRNA database (http://www.mirbase.org) to verify that the miRNA location is also conserved inswitchgrass.

Construction of a small RNA library, sequencing and

sequence analysis

Three-month-old seedlings and flowers from adult plants(cultivar Alamo) were harvested, and total RNA was extractedusing Trizol reagent, following the manufacturer’s instructions.Equal molar amounts of total RNA from the seedlings andinflorescence were pooled and used for small RNA libraryconstruction as described (Sunkar et al., 2008). The PCR productunderwent pyrosequencing, and 21,999 raw sequences wereobtained. Sequence analysis was performed as described pre-viously (Jagadeeswaran et al., 2009b; Sunkar et al., 2008). In brief,small RNAs between the adaptors were extracted, and sequencesshorter than 17 nt and longer than 28 nt were removed. For theremaining small RNAs, duplicates were removed, and thefrequency of the unique sequences was recorded. Degradationproducts from ribosomal RNAs, transfer RNAs, small nuclear RNAsand small nucleolar RNAs, as well as mRNAs were discardedbefore further analysis. The unique small RNAs aligned to RepBase(version 13.04, obtained from http://www.girinst.org) and knownnon-coding RNAs (1924 reads) (rRNAs, tRNAs, snRNAs, snoRNAs,etc., obtained from http://www.sanger.ac.uk/Software/Rfam/ftp.shtml) were discarded. Similarly, unique reads corresponding tomRNAs (1152 reads) from switchgrass (available ESTs at the NCBI)as well as other plant species were regarded as potentialdegradation products and discarded. The remaining small RNAswere considered putative small RNAs and were further processedto determine whether these were miRNAs or siRNAs. ConservedmiRNA homologs were identified by searches against miRBase.

Growth conditions and tissue selection for small RNA blot analysis

Seedlings of the switchgrass cultivar Alamo were grown ingrowth chambers with a 16/8 h day/night cycle at 21 1C for 8–10weeks, and adult plants were grown in the greenhouse. Twodifferent sets (upper and lower) of leaves from seedlings andmature plants (top-most 3 leaves designated as upper leaves, andbottom-most 3 leaves designated as bottom leaves), stems fromboth the seedlings and mature plants, roots and inflorescencewere collected, immediately frozen in liquid nitrogen and storedat �80 1C.

Nutrient stress treatments

Seeds were allowed to germinate on wet vermiculite and laterseedlings were transferred to 96-well PCR plates containing holesin their wells. Seedlings were grown in the presence of controlmedia for 4 weeks, and then transferred to media containingdifferent levels of sulfate or phosphate (0.02, 0.2, or 2.0 mM) for5 days. The media were replaced daily. After treatment, seedlings

and their targets in switchgrass, a model biofuel plant species. J

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were collected and frozen in liquid nitrogen, and RNA wasextracted.

Small RNA blot analysis

Small RNA blot analysis was performed as described (Sunkarand Zhu, 2004). In brief, low-molecular-weight (LMW) RNA wasisolated from the total RNA samples. Twenty micrograms of LMWRNA was resolved on a denaturing 15% acrylamide/8 M urea gel,transferred to a hybond-N+ (Amersham) membrane and probedwith the labeled 32-P DNA oligonucleotides complementary tothe miRNA sequence. Blots were pre-hybridized for at least 1 hand hybridized overnight with PerfectHYB+ buffer (Sigma) at38 1C. Blots were washed and exposed to a phosphoscreen. Imageswere acquired by scanning the phosphoscreen using a Typhoonscanner.

Target predictions and validation by modified 50-RACE assay

Target predictions involved the use of the mature miRNAsequences identified in switchgrass. These miRNA sequences wereused as a query to search for the complementary hits among theavailable ESTs from switchgrass. The criteria used for the targetpredictions was r4 mismatches between the miRNA and itsmRNA target, with no mismatches allowed in positions 10 and 11,as was suggested previously (Schwab et al., 2005). Annotation forthe target EST was determined by searching for homologoussequences in rice or other plants (http://rice.plantbiology.msu.edu/blast.shtml). A modified 50-RACE assay was performed

Table 1Identified homologs of conserved miRNAs and tasiRNAs in switchgrass by sequencing

miRNA miRNA sequence (50-30)

miR156a,b UGACAGAAGAGAGUGAGCAC

miR156e UGACAGAAGAGAGCGAGCAC

miR156f AGACAGAAGAGAGUGAGCAC

miR156k UGACAGAAGAGAGAGAGCAC

miR159b UUUGGAUUGAAGGGAGCUCUG

miR160 UGCCUGGCUCCCUGUAUGCCA

miR164a UGGAGAAGCAGGGCACGUGCA

miR164c UGGAGAAGCAGGGUACGUGCA

miR166 UCGGACCAGGCUUCAUUCCCC

miR167b UGAAGCUGCCAGCAUGAUCUA

miR168 UCGCUUGGUGCAGAUCGGGAC

miR169a CAGCCAAGGAUGACUUGCCGA

miR169c CAGCCAAGGAUGACUUGCCGG

miR169d CAGCCAAGGAUGACUUGCCUA

miR169b UAGCCAAGGAUGACUUGCCGG

miR169k UAGCCAAGGAUGACUUGCCUU

miR171g UGAUUGAGCCGUGCCAAUAUC

miR172a AGAAUCUUGAUGAUGCUGCAU

miR172c ACUUGAUGAUGCUGCAGU

miR172b GGAAUCUUGAUGAUGCUGCAU

miR172d AGAAUCCUGAUGAUGCUGCAG

miR319 UUGGACUGAAGGGUGCUCCC

miR393 CUCCAAAGGGAUCGCAUUGAU

miR394 UUGGCAUUCUGUCCACCUCC

miR395n CUGAAGUGUUUGGGGGAACUC

miR396n UUCCACAGCUUUCUUGAACUG

miR397 UCAUUGAGUGCAGCGUUGAUG

miR398n UGUGUUCUCAGGUCACCCCUU

miR399 UGCCAAAGGAGAUUUGCCCUG

miR408 CUGCACUGCCUCUUCCCUGG

miR437 AAAGUUAGAGAAGUUUGACUU

miR444 UGCAGUUGCUGCCUCAAGCU

miR528 UGGAAGGGGCAUGCAGAGGAG

Tas3-siRNA UUGGGAGGAUUGAUAGGCGCUA

n miRNA families confirmed using small RNA blot analysis, but neither were found

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

according to Sunkar et al. (2005), and the amplified PCR productswere cloned and sequenced.

Results and discussion

In general, conserved miRNAs can be identified by computa-tional approaches or experimental approaches such as directcloning of small RNAs or detection using a probe complementaryto the conserved miRNA homolog. Here, we used both computa-tional and experimental approaches for identification of miRNAsin switchgrass.

Computational identification of conserved miRNAs in switchgrass

For computational identification of a complete set of conservedmiRNAs, the availability of complete genome sequence is a pre-requisite. If the complete genome is unavailable, the availablelarge genomic fragmented data in the form of genomic surveysequences (GSS), whole-genome shotgun reads (WGS), high-throughput genomic sequences (HTGS) and non-redundantnucleotide sequences (NR) have been used (Sunkar and Jagadees-waran, 2008). Analysis of ESTs has also revealed several conservedmiRNAs from diverse plant species (Sunkar and Jagadeeswaran,2008; Zhang et al., 2006). Currently no GSS, WGS, or HTGSsequences were available for switchgrass. Thus, for computationalidentification of conserved miRNAs, we relied on �436,535switchgrass ESTs deposited in the NCBI database and this couldbe a limitation in identifying complete set of conserved miRNAs inswitchgrass.

a small RNA library, computational approach as well as detection-based analysis.

Cloning frequency Computationally predicted

7 +

23

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in the small RNA library nor identified using computational strategy.

and their targets in switchgrass, a model biofuel plant species. J

ARTICLE IN PRESS

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On the basis of mature miRNA sequence similarity, the miRNAsare grouped into families, with members often varying by 1–2 nt.Currently 21 miRNA families are conserved between dicotyledo-nous and monocotyledonous plants (Jones-Rhoades et al., 2006).Additionally, a few monocot-specific miRNA families, includingmiR437 and miR444, have been reported (Lu et al., 2008; Sunkaret al., 2005). A total of 16 conserved miRNA families (miR156,miR159, miR160, miR166, miR167, miR169, miR171, miR319,miR394, miR397, miR399, miR408, miR444, miR437, and miR528)were identified using the computational strategy (Table 1). Ofthese, miR156, miR159, miR160, miR164, miR166, miR167,miR169, miR171, miR319, miR394, miR397, and miR399 areconserved between monocotyledonous and dicotyledonousplants, whereas miR437, miR444, and miR528 are conservedonly among monocotylednous plants (Fig. 1). The predicted fold-back structures for these miRNA families share similar featureswith their counterparts in other plant species (Fig. 1).

Fig. 1. Predicted hairpin-like structures using primary MIRNA transcripts of the conserve

in each hairpin-like structure.

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

Construction, sequencing and sequence analysis of

a small RNA library

Because our computational approach was limited by the lackof availability of the sequenced genome and limited number ofavailable ESTs, the identification of all known conserved miRNAfamilies in switchgrass was not possible. Cloning can identify bothconserved and novel species-specific miRNAs, if any. By sequen-cing a small RNA library, we obtained 21,999 small RNAsequences ranging from 18 to 27 nt (Fig. 2). After the removal ofredundant sequences, 15,637 unique sequences were obtained(data not shown). Of these, approximately 1100 small RNAsappeared to be degraded products from protein-coding mRNAs,and another 2084 sequences were mapped to other non-codingRNA sequences, which were eliminated before further analysis.For the remaining unique small RNAs, homology searches againstmiRBase resulted in the identification of 34 conserved miRNAs

d miRNAs in switchgrass. The mature miRNA sequence is underlined and italicized

and their targets in switchgrass, a model biofuel plant species. J

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6000

5000

4000

3000

2000Fre

quen

cy

1000

018 19 20 21 22 23 24 25 26 27

Size (nucleotides)

Fig. 2. Distribution of small RNA sequences ranging from 18 to 27 nt.

Fig. 3. Predicted hairpin-like structures using primary MIRNA transcripts of the

novel candidate miRNAs. The mature miRNA sequence is underlined and italicized

in each hairpin-like structure.

Fig. 1. (Continued)

J. Matts et al. / Journal of Plant Physiology ] (]]]]) ]]]–]]] 5

belonging to 16 miRNA families in switchgrass (miR156, miR159,miR164, miR166, miR167, miR168, miR169, miR171, miR172,miR319, miR399, miR408, miR442, miR444, and miR528). Of the21,999 raw sequences, only 269 small RNA sequences wereidentified as being homologs of conserved miRNA families inswitchgrass (Table 1). Thus, only a small fraction of the total smallRNAs were miRNAs, and the remaining sequences are consideredendogenous siRNAs, whose identity remains largely unknown.

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

The frequencies of different miRNAs in the library variedgreatly, and some miRNAs appeared as many as 90 times, whereasothers were found only once. Of 269 miRNA homologs found inthe library, the miR172 family was the most abundant, with a

and their targets in switchgrass, a model biofuel plant species. J

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seedlings Adult seedlings Adult

miR156miR164

miR172 miR166

miR169miR160

miR159miR171

miR398

miR167 miR319

miR396miR408

miR393miR444

U6

miR528

U6

Low

er L

eave

s

Upp

er L

eave

s

Low

er L

eave

s

Upp

er L

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s

Stem

-see

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gs

Stem

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Infl

ores

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Low

er L

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s

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er L

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s

Low

er L

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s

Upp

er L

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s

Stem

-see

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gs

Stem

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Infl

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e

Fig. 4. Expression analysis of conserved miRNAs in different tissues of switchgrass seedlings and adult plants.

miR395

U6

2.0

miR399

U6

0.2 0.02 mM Phosphate

2.0 0.2 0.02 mM Sulphate

Fig. 5. Response of miR395 and miR399 to sulfate- and phosphate-deprived

conditions, respectively, in switchgrass.

J. Matts et al. / Journal of Plant Physiology ] (]]]]) ]]]–]]]6

count of 132. Within the miR172 family, miR172a appeared90 times and thus is the most abundantly expressed variant of themiR172 family. miRNA, miR156 is the second most abundantmiRNA family, with a count of 53 in our sequences. The frequencyof the remaining conserved miRNAs was relatively low. Forinstance, miR168, miR393 and miR159 families were representedby 14, 13 and 11 times, respectively in our library. Six miRNAsbelonging to five miRNA families (miR164c, miR169d, miR169k,miR172d, miR408, and miR444) appeared only once in the library(Table 1). The members of 8 conserved miRNA families (miR160,miR162, miR390, miR394, miR395, miR396, miR397, and miR398)were not found in the library but the expression of four of thesewere confirmed in swtichgrass using small RNA blot analysis(see below).

In plants, TAS3-siRNAs are highly conserved, and theirbiogenesis depends on miR390, a conserved miRNA (Allen et al.,2005). We could not identify the miR390 sequence in our smallRNA library or by a computational approach. Nevertheless, wecloned TAS3-siRNA from switchgrass (Table 1). Its biogenesisdepends on miR390 in other plants (Allen et al., 2005; Jagadees-waran et al., 2009b), which suggests that miR390 is expressed inswitchgrass. Conserved TAS3-siRNA biogenesis depends strictly

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

on miR390-guided cleavage on the TAS3 primary transcript,which in turn is converted into double-stranded RNA. This dsRNAis further processed by the DCL4 and TAS3-siRNAs are generated(Allen et al., 2005). This process likely occurs in switchgrass aswell.

Additionally, we could identify 4 candidate miRNAs by cloninga small RNA and predicted fold-back structure for their primarymiRNA transcripts found in the ESTs from switchgrass (Fig. 3).Novel miRNAs can be more confidently identified if miRNAn

sequence appears in the small RNA library (Meyers et al., 2008).miRNAn sequences are relatively less abundant than are theirmiRNA counterparts and require deeper sequencing. Thus, agreater sequencing depth of small RNA libraries from switchgrasswill validate whether these 4 belong to novel switchgrass-specificmiRNAs or not.

Expression analysis

Analysis of miRNA expression in Arabidopsis, rice and Medicago

truncatula revealed many miRNAs expressed in only certaintissues and cell types, only during certain developmental stages,or with altered expression in response to stress (Jagadeeswaranet al., 2009b; Lu et al., 2005; Sunkar and Zhu, 2004; Sunkar et al.,2005, 2007). Furthermore, previous reports showed the conservedmiRNAs with divergent expression patterns in different plantspecies (Jagadeeswaran et al., 2009b; Lu et al., 2005; Subramanianet al., 2008). We analyzed the expression patterns of 16 miRNAs indifferent organs and developmental stages of switchgrass. Generalabundance based on signal intensity suggested that the expres-sion of nine miRNAs (miR156, miR160, miR172, miR171, miR167,miR166, miR164, miR159, and miR319) was relatively higher thanthat of the other seven miRNAs tested. Most miRNA families, suchas miR166, miR159, miR171, miR167, miR160, miR164, andmiR398 showed only minor differences in expression betweentissues (Fig. 4). By contrast, some miRNAs showed tissue-specificexpression patterns. For instance, the level of miR156 wasabundant in both the upper and the lower sets of seedlingleaves but was almost undetectable in similar sets of mature plantleaves (Fig. 4). In contrast, the level of miR172 was abundant inthe 2 sets of mature plant leaves but was almost absent in

and their targets in switchgrass, a model biofuel plant species. J

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upper seedling leaves, with much diminished levels in lowerseedling leaves (Fig. 4). This opposite pattern of expression formiR156 and miR172 is consistent with their reported roles inArabidopsis (Chen 2004; Wang et al., 2009; Wu et al., 2009;Yamaguchi et al., 2009). Arabidopsis miR156 plays anindispensable role in phase transitions from juvenile to adult bytargeting SPL transcription factors (Wang et al., 2009; Wu et al.,2009; Yamaguchi et al., 2009). In contrast, miR172 appears to playa role in the vegetative-to-reproductive phase transition inArabidopsis. Surprisingly, in switchgrass, the expression ofmiR172 was almost undetectable in inflorescence tissue,whereas miR172 was abundantly detected in flowers ofArabidopsis (Chen, 2004).

The miRNA, miR160 had signals at two different sizes (21 and22/23 nt), both ubiquitously expressed. The level of miR393 wasabundant only in inflorescence, although it could be detected instems of mature plants and the upper leaves of both seedlings andmature plants but was almost undetectable in roots, stems andupper leaves of mature plants (Fig. 4). miRNA, miR319 wasabundantly expressed in inflorescence and stems of both seed-lings and mature plants and in the upper leaves of seedlings(Fig. 4). miRNA, miR319 is known to play an important role in leafmorphogenesis by targeting teosinte branched 1, cycloidea, PCF(TCP)-domain protein family (TCP) factors in Arabidopsis (Palatniket al., 2003). However, its detection in inflorescence and stemsstrongly suggests additional roles for miR319 in switchgrass. Theexpressions of miR408 and miR528 were approximately similar,being detected exclusively in inflorescence, mature stem andlower leaves of mature plants (Fig. 4). The expression of miR396was detected only in upper leaves and stems of seedlings and ininflorescence, but was almost absent in other tissues. AlthoughmiR171 expression could be detected in all tissues analyzed, itwas abundant in upper leaves of both seedlings and mature plantsand in stems of seedlings, as well as in inflorescence.

Interestingly, the expression of miR444 was distinct betweenleaves of seedlings and mature plants (Fig. 4). It was abundant inleaves from seedlings but was low in similar sets of leaves frommature plants. The miRNA, miR444 was differentially expressedin the upper and the lower leaves of adult plants (Fig. 4). Stemsfrom mature plants showed much higher levels of miR444 thandid stems of seedlings. The expression of miR444 seemed to below in roots and extremely low in inflorescence. These results

Table 2Predicted targets for conserved microRNAs in switchgrass.

microRNA family Predicted target(s) (EST accession number) Target

156/157 FE626923; DN143702 SPB-lik

159 FE656043; GD051711 MYB tr

160 FL913173; FL738979; FE606478 Auxin

162 FL812781 DCL1

164 FE608722; FL846228 NAC tr

165/166 FE606478; GD002178; FL954559 HD-zip

167 DN141844; GD032712; GD007307 Auxin

168 FL904157; FL818096 Argoun

169 FL965734 CBF (C

170/171 FL923024; FL910918 Scarec

172 FL945982; FL940492; FE642476 AP2 do

319 FE603736; FL985594 TCP tra

390 FL692881 Leucin

393 DN143813 F-box

394 FL978450 F-box

395 FL710917; FL910325 Sulfate

397 FL753322 Laccas

399 FL811879; FL997840 Ubiqui

408 FL942386 Plantac

444 FL979804 MADS

528 GD052089 Unkno

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

suggest a dynamic regulation of miR444 expression in differenttissues and in different developmental stages in switchgrass.Interestingly, miR444 is a monocot-specific miRNA and targets 4MADS box transcripts in rice (Li et al., 2010; Lu et al., 2008;Sunkar et al., 2005). Taken together, the expression analysisindicated a dynamic regulation of several miRNAs in differenttissues of seedlings and mature switchgrass plants.

Analysis of miR395 and miR399 expressions in switchgrass

The miRNAs, miR395 and miR399 are widely conserved acrossdifferent plant species (Sunkar and Jagadeeswaran, 2008; Zhanget al., 2006). They are induced under sulfate- and phosphate-deprived conditions, respectively, in Arabidopsis and M. truncatula

(Fujii et al., 2005; Jagadeeswaran et al., 2009b; Jones-Rhoades andBartel, 2004). If this is also the case in switchgrass, these twomiRNAs were unlikely to be retrieved from our library becausethe library was generated from plants grown with optimal levelsof nutrients. However, miR399 homolog was identified usingcomputational approach (Table 1 and Fig. 1), whereas miR395could not be identified in our computational or cloning strategies.Analysis of miR395 expression in switchgrass indicated its basallevels to be relatively high. However, under low-sulfate condi-tions, the miR395 level was slightly upregulated (Fig. 5). Similarly,miR399 expression was detected in plants grown with optimallevels of nutrients and only slightly changed under phosphate-deprived conditions (Fig. 5). Taken together, the analysis ofmiR395 and miR399 expressions in switchgrass suggesteddifferential regulation, which could be attributed, at least inpart, to the plant adaptation to marginal soils with low nutrientavailability under natural conditions.

Target predictions and their validation

Most plant miRNA sequences display near perfect comple-mentarily with their target mRNAs, and this characteristic hasbeen used to predict potential targets for miRNAs by a computa-tional approach (Jones-Rhoades and Bartel, 2004; Rhoades et al.,2002). To predict potential targets for miRNAs identified inswitchgrass, the EST database (NCBI) was searched for switch-grass mRNAs that possess miRNA complementary sites (Table 2).

gene family

e protein

anscription factor and hypothetical protein

response factor; hypothetical protein; and SMART domain containing protein

anscription factors

-like; HEAT repeat family protein; and unknown protein

response factor and unknown proteins

ate1-like

CAAT binding factor)-HAP2 like protein

row transcription factors

main containing proteins

nscription factor and unknown protein

e rich repeat protein

protein (TIR1 homolog)

protein

transporter; and bifunctional 3’-phosphoadenosine 5’-phosphosulfate synthase

e

tin conjugating enzyme protein and transposon

yanin

box containing protein

wn proteins

and their targets in switchgrass, a model biofuel plant species. J

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Fig. 6. Experimental validation of predicted miRNA targets in switchgrass.

J. Matts et al. / Journal of Plant Physiology ] (]]]]) ]]]–]]]8

Targets were predicted for most of the conserved miRNAs inswitchgrass (Table 2). The predicted targets include homologs ofknown targets for conserved miRNAs and novel targets. Twelveof the conserved miRNA families are predicted to targettranscription factors in Arabidopsis (Jones-Rhoades et al., 2006).In switchgrass, several transcription factor families, includingsquamosa promoter binding (SBP) transcription factors, MYBtranscription factors, TCP factors, NAC domain containing tran-scription factor, auxin response factors (ARFs), scarecrow-liketranscription factors, apetala 2 (AP2)-like transcription factor,MADS box proteins, and CCAAT binding factors (CBF) werepredicted as targets for miR156, miR159, miR319, miR164,miR160/167, miR171, miR172, miR444, and miR169 families,respectively. Other predicted targets include proteins such astransport inhibitor response 1 (an F-box protein) for miR393,argonaute 1-like for miR168, plantacyanin for miR408, ubiquitinconjugating enzyme for miR399, and transcripts that code forunknown proteins. To validate the predicted targets, we used50-RACE to map the miRNA-guided cleavage site on target mRNAs.Four predicted targets were confirmed as miRNA targets inswitchgrass (Fig. 6). These validated targets include thetranscription factors NAC for miR164, HD-zip for miR166, SPLfor miR156 and AP2-like for miR172.

Switchgrass has attracted much attention as a source of biofuelplant species because it can grow well even on marginal lands andcan tolerate drought stress. miRNAs have emerged as criticalregulators of gene expression important not only for normalgrowth and development but also in adaptation to abiotic andbiotic stresses. Similarly, relatively high basal levels of miR395and miR399 in switchgrass suggest that this plant species isadapted to poor soils with low levels of sulfate and phosphate.Here we sought to understand more about the basic biology of thetraits of switchgrass that control its growth and stress tolerancecharacteristics. Furthermore, identification of miRNAs in switch-grass is also of biotechnologically important, particularly inimproving biomass characteristics. For instance, identification ofmiR156, which has been shown to improve biomass accumulationin other plant species, is an attractive target for the improvementof switchgrass biomass production. As expected, most conservedmiRNA targets in switchgrass are homologous targets that includetranscription factors (SPL, AP2, MYB, HD-Zip, CBF, SCL, and MADSbox factors) and function in diverse aspects of plant growth anddevelopment. Other targets such as F-box protein (possibly a TIR1homolog) and ARF are involved in hormone (auxin)-controlled

Please cite this article as: Matts J, et al. Identification of microRNAsPlant Physiol (2010), doi:10.1016/j.jplph.2010.02.001

growth and development. The roles of laccase are relativelyunknown, but it is thought to function in lignin biosynthesis orstress defense responses, whereas planatcyanin has been shownto play role in reproduction and seed development. Thus thepredicted targets are likely to function in diverse processesregulating switchgrass development, reproduction and stressresponses. Our identification of all conserved miRNA familiesand at least one miRNA target for most miRNAs in switchgrass canserve as a basis for future functional genomics approaches.

Acknowledgment

This work has been supported, in part, by the NSF EPSCoRaward EPS0814361 and the Oklahoma Agricultural ExperimentStation, to R. Sunkar.

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