Plant Cell, Tissue and Organ Culture (PCTOC)

, Volume 105, Issue 2, pp 233–242

Identification and validation of conserved microRNAs along with their differential expression in roots of Vigna unguiculata grown under salt stress

Authors

  • Sujay Paul
    • Division of Plant Biology, Bose Institute
  • Anirban Kundu
    • Division of Plant Biology, Bose Institute
    • Division of Plant Biology, Bose Institute
Original Paper

DOI: 10.1007/s11240-010-9857-7

Cite this article as:
Paul, S., Kundu, A. & Pal, A. Plant Cell Tiss Organ Cult (2011) 105: 233. doi:10.1007/s11240-010-9857-7

Abstract

MicroRNAs (miRNAs) are 20–24 nucleotide long non-coding RNAs known to play important regulatory roles during plant development, organ morphogenesis, and stress responses by controlling gene expression. Although Vigna unguiculata (cowpea) is an economically important salt sensitive member of legumes, very little is known about the conserved miRNAs and their expression profile during salinity stress in this plant. In the present study using comparative genomic approach and following a set of strict filtering criteria we have identified 18 conserved V. unguiculata miRNAs belonging to 16 distinct miRNA families. Using these potential miRNA sequences 15 potential target genes were predicted and all of them were identified as transcription factors. Seven of these predicted V. unguiculata miRNAs were experimentally validated in the root tissues and found to be up-regulated during salt stress as revealed by quantitative real time PCR (qRT-PCR). Perfectly cleaved Auxin response factor (ARF), the target transcript of V. unguiculata miR160 was detected successfully by modified 5′ RNA ligase-mediated rapid amplification of cDNA ends (RLM-RACE) method.

Keywords

MicroRNASalt stressVigna unguiculata (cowpea)miRNA targetsqRT-PCR5′ modified RLM-RACE

Abbreviations

EST

Expressed sequence tag

GSS

Genomic survey sequence

RISC

RNA induced silencing complex

MFE

Minimum folding free energy

MFEI

Minimum folding free energy index

RLM-RACE

RNA ligase-mediated rapid amplification of cDNA ends

qRT-PCR

Quantitative real time PCR

DFCI

Dana Farber Cancer Institute

SBP

Squamosa promoter binding protein

SPL

Squamosa promoter binding protein-like protein

ARF

Auxin response factor

TCP

Teosinte branched1-Cycloidea-Pcf

CBF

CCAAT-binding transcription factor

NFY

Nuclear factor Y

AP2

APETALA2

AGO1

Argonaute1

TC

Tentative contigs

snRNA

Small nuclear RNA

Introduction

Vigna unguiculata (L.) Walp. (cowpea) is one of the important leguminous crops in the semi-arid tropics covering Asia, Africa, southern Europe, Central and South America (Singh et al. 1997). Cowpea has excellent nutritional qualities containing 24–26 percent protein and well balanced essential amino acid composition with high amounts of leucine, lysine and methionine (Bressani 1985). It is also capable of enhancing soil fertility through biological nitrogen fixation (Martins et al. 2003). However, legume production has been highly affected by salinity stress (Bayuelo-Jimenez et al. 2002; Wang et al. 2003; Chen et al. 2007), the most severe abiotic stress; which can limit growth and development of plants (Munns 1993). MicroRNAs have a great role in gene regulation but very limited information is available to date about V. unguiculata microRNAs and their expression pattern during stress.

MicroRNAs (miRNAs) are a class of small, non-coding, evolutionarily conserved RNAs with about 20–24 nucleotides in length (Bonnet et al. 2004). They play crucial roles in post-transcriptional gene regulation by complementing the target mRNAs and causing transcriptional repression or target mRNA degradation (Bartel 2004). In plants, RNA polymerase II enzyme transcribes miRNA genes into long primary transcripts (pri-miRNAs; Chen 2005). This pri-miRNAs are subsequently trimmed by ribonuclease III-like Dicer (DCL1) enzyme producing miRNA precursors (pre-miRNAs) with stem-loop (hairpin) structure(s). Subsequently, a second cleavage by DCL1 at the loop region of the hairpin produces a short double-stranded RNA (dsRNA). One of these strand acts as mature miRNA (Kurihara and Watanabe 2004). The mature miRNA gets incorporated into the RNA induced silencing complex (RISC) and guides RISC to complementary mRNA targets for degradation (Lin et al. 2005). Lots of investigations indicated that majority of characterized miRNAs are involved in plant development (Chen 2004), signaling (Yoshikawa et al. 2005) and organ morphogenesis (Kidner and Martienssen 2005). Recently, it has been reported that miRNAs are also hypersensitive to abiotic or biotic stresses. MicroRNAs possibly regulate gene expression at the post-transcriptional level thus contribute to the stress-induced changes in proteins (Sunkar et al. 2006; Lu et al. 2008; Zhou et al. 2008; Zhang et al. 2008a, b; Ding et al. 2009).

The most common experimental approach to find out novel miRNAs is by direct cloning (Lu et al. 2005; Zhang et al. 2006a), in which small RNAs are first isolated by size fractionation in a denaturing polyacrylaminde gel. Then RNA adapters are ligated to these RNAs at their respective 5′ and 3′ ends. Subsequently, these fragments are reverse transcribed into cDNAs and at last, the first strand cDNAs is amplified by PCR and sequenced (Lu et al. 2005). However, it is very difficult to detect miRNAs that are expressed at low level following this technique. To overcome this limitation, an alternate approach is in vogue, here the novel mature miRNAs and their precursors are first identified by screening the Expressed Sequence Tag (EST)/Genome Survey Sequence (GSS) database of a particular species (Wang et al. 2004; Liang et al. 2007) and then validated by cloning, Northern blotting or quantitative real time PCR (Liang et al. 2007; Feng et al. 2009). Since miRNAs are very much conserved in nature this approach works well, for those species which have sufficient EST/GSS sequences available to predict and validate novel miRNAs (Wang et al. 2004; Liang et al. 2007) that usually cannot be detected by the direct cloning approach due to their low abundance. However recent advances in high-throughput or next generation sequencing strategies can also identify low abundance or tissue specific miRNAs (Fahlgren et al. 2007; Wei et al. 2009) but it requires high technical expertise.

Materials and methods

Reference set of miRNAs

To identify potential V. unguiculata miRNAs, a set of plant miRNAs has been compared with the V. unguiculata EST and GSS database. The set of miRNAs and their precursors used, downloaded from miRBase (version 14.0, September, 2009; http://microrna.sanger.ac.uk/sequences/index.shtml) consisted of 402 known mature miRNA sequences including Arabidopsis thaliana (199) and 4 members of Fabaceae family like Glycine max (85), Lotus japonicus (2), Medicago truncatula (108) and Phaseolus vulgaris (8). Experimentally validated mature miRNA sequences of these plants were mainly used in this computational prediction study.

EST and GSS source for V. unguiculata

V. unguiculata ESTs and GSSs were obtained from NCBI Genbank (http://www.ncbi.nlm.nih.gov/). At present a total number of 2,41,606 sequences including 1,87,660 ESTs and 54194 GSSs of V. unguiculata are deposited in NCBI Genbank.

Prediction of potential V. unguiculata miRNAs and their precursors (pre-miRNAs)

The methodology used to search for potential miRNAs in V. unguiculata is illustrated graphically in Fig. 1. The method used in this study was described by Zhang et al. (2006b) with some modification. Briefly, the known mature miRNA sequences of Arabidopsis thaliana and of different genus of Fabaceae family deposited in latest version of miRBase were subjected to a BLASTn search against V. unguiculata EST and GSS databases using BLASTn 2.2.22 (19 Oct 2009; Altschul et al. 1997). Adjusted BLASTn parameter settings were as follows: expected values were set at 1,000; low complexity was chosen as the sequence filter; and all other parameters were used as default. EST and GSS sequences showing 0–3 nucleotide mismatches compared with the query miRNA sequence were chosen manually. The repeat sequences and those coding proteins were removed. Web-based software MFOLD 3.2 (Zuker 2003) which is publicly available at (http://frontend.bioinfo.rpi.edu/applications/mfold/cgi-bin/rna-form1.cgi) has been used to predict the secondary structures of candidate (pre-miRNA) sequences. The parameters were adjusted as RNA sequence (linear), folding temperature (37°C), ionic condition (1 M NaCl with no divalent ions), percent suboptimality number (5); maximum interior/bulge loop size (30), and all others with default values. The lowest free energy structures were selected for manual inspection, as illustrated by Reinhart et al. (2002). The potential pre-miRNAs should meet all of the following criteria (Zhang et al. 2006c; Meyers et al. 2008) as described previously: (a) predicted mature miRNAs have 0–3 nt mismatches compared with the query sequences; (b) the secondary structure of the candidate sequences should have the stem-loop structure that contains the mature miRNA sequence within one arm and no loop or break in the mature miRNA sequences; (c) the potential miRNA sequence is not located on the terminal loop of the hairpin structure; (d) the predicted stemloop candidates should have higher Minimum folding free energy indexes (MFEIs) and negative Minimum folding free energies (MFEs). The formula for calculating MFEI is as follows:
$$ {\text{MFEI}} = \left[ {\left( {{\text{MFE}}/{\text{length of the RNA sequence}}} \right)* 100} \right]/\% {\text{ GC content}} $$
where MFE denotes the negative folding free energy (ΔG); (e) miRNA should have six or less mismatches with the opposite miRNA* sequences; (f) the A + U contents of candidate pre-miRNA should be >30%.
https://static-content.springer.com/image/art%3A10.1007%2Fs11240-010-9857-7/MediaObjects/11240_2010_9857_Fig1_HTML.gif
Fig. 1

Schematic representation of Vignaunguiculata miRNA search procedure

Prediction of potential targets

To determine the potential targets of predicted miRNAs in V. unguiculata, we used BLASTn algorithm against Cowpea (Version 1.0) Dana Farber Cancer Institute (DFCI) Gene Indices (http://compbio.dfci.harvard.edu/tgi/). Previous study has shown that most known miRNAs bind to the protein coding region of their mRNA targets with perfect or near perfect sequence complementarity and degrade or repress the target mRNA (Wang et al. 2004). We followed previously employed criteria to predict potential mRNA targets of given plant miRNAs (Zhang et al. 2007; Yin et al. 2008) and they are: (a) no more than 4 mismatches were allowed at complementary sites between miRNA sequence and potential mRNA targets, (b) no mismatch between positions 10 and 11 (assumed to be cleavage site), no more than 1 mismatch between positions 1 and 9, no more than 2 mismatches at other positions and no gaps between miRNA and target mRNA at the complementary sites were allowed.

Plant materials and stress treatment

Vigna unguiculata (Cv. Local) seeds after surface sterilization in 70% ethanol for 2 min were rinsed twice in deionized water and then placed on water-moistened filter papers in sterile petridishes for germination at 28 ± 1°C and 70% of relative humidity (RH). Seeds germinated in 1 day were transplanted into earthen pots filled with sterile and moist vermiculite and grown in a greenhouse at 25–27°C. Uniform seedlings with two leaves were transferred into a sterile conical flask containing 100 ml of Hoagland nutrient solution (pH 6.5; Hoagland and Arnon 1950). Plants were grown in the described hydroponic system in a greenhouse with controlled environmental conditions (25°C, 70% humidity and natural illumination). The nutrient solution was replaced every 3 days and the conical flask was shaken daily to ensure aeration in the root system. When the first trifoliate leaf became flat, plants were transferred into either a nutrient solution containing 200 mM NaCl for salt stress treatment or the nutrient solution without NaCl as mock. The roots of ten stressed plants were harvested at 12 h after salt stress treatment; the roots of untreated control (mock) were also harvested at the same time point. Harvested roots were immediately frozen in liquid N2 and stored in −80°C freezer until used for RNA isolation.

Small RNA and total RNA isolation

Small RNA and total RNA were isolated from roots of mock and stress treated plants using mirPremier microRNA Isolation Kit (Sigma-Aldrich) and RNeasy Mini Kit (Qiagen) respectively, according to the manufacturer’s instructions. The quality and quantity of isolated RNA samples were measured using a Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies, USA) and stored at −20°C.

Polyadenylation and cDNA synthesis

Small RNA (1 μg) isolated both from roots of mock and stress-treated plants were polyadenylated and reverse transcribed at 37°C for 1 h in 10 μl reaction mixture using Mir-X miRNA First-Strand Synthesis kit (Clontech) following manufacture’s instructions. The reaction mixture contains 1× mRQ Buffer and 1 μl of mRQ enzyme mix provided with the kit, after 1 h the reaction was terminated at 85°C for 5 min and finally the volume was made up to 100 μl with deionized water.

Detection and cloning of predicted miRNAs

To detect the predicted miRNAs, the obtained cDNA from the previous step was amplified by GeneAmp PCR system 2400 (Perkin Elmer) using entire predicted miRNA sequence as sense primer and mRQ 3′ primer provided with Mir-X miRNA qRT-PCR SYBR kit (Clontech) as antisense primer. The resulting PCR products were checked on 4% agarose gel with EtBr staining and then the gel slice containing desired fragments around 70 bp were excised and eluted using Qiaquick gel elution kit (Qiagen). Finally, The DNA fragments were cloned in pJET1.2 cloning vector provided with CloneJET PCR Cloning Kit (Fermentas) and sequenced (ABI Prism 3130xl DNA sequencer).

Analysis of mature miRNAs expression pattern during salt stress by quantitative real-time PCR (qRT-PCR)

Analysis of the expression pattern of detected mature miRNAs during salt stress was performed by iQ5 quantitative real-time PCR system and iQ5 Optical system software (Bio-Rad) using Mir-X miRNA qRT-PCR SYBR kit (Clontech) following manufacturer’s instructions. Briefly, 25 μl PCR reaction mixtures were prepared and each contained 1× SYBR Advantage Premix, 1× ROX dye, 0.2 μM each of sense and antisense primers as indicated above and 2 μl of the first strand cDNA. The reactions were incubated in a 96 well plate at 95°C for 2 min, followed by 40 cycles of 95°C for 10 s and 60°C for 20 s. This cycle was followed by a melting curve analysis ranging from 56 to 95°C, with temperature increasing steps of 0.5°C every 10 s. Melting curves for each amplicon were observed carefully to confirm the specificity of the primers used. Relative expression levels for each sample were obtained using the “comparative Ct method” (Schmittgen and Livak 2008). The threshold cycle (Ct) value obtained after each reaction was normalized to the Ct value of U6 snRNA (U6 snRNA primer was provided with the kit) whose expression was consistent across the conditions. All reactions were conducted in triplicate.

miRNA target validation by 5′ RLM-RACE

To experimentally validate the cleavage sites of computationally predicted targets of the detected miRNAs, we have used a modified version of 5′ RLM-RACE approach (Wei et al. 2009; Arenas-Huertero et al. 2009). One μg of total RNA isolated from stress treated root was subjected to a 5′ RACE reaction using FirstChoice RLM-RACE kit (Ambion) omitting calf intestine alkaline phosphatase and tobacco acid pyrophosphatase treatments. For each Tentative Contig (TC) two gene specific reverse primers (5′ RACE gene specific outer and inner primer) were designed. The PCR reaction and cycling conditions were setup following the manufacture’s protocol. Annealing temperatures were adjusted for specific primers. Finally, the nested PCR products were cloned into pJET1.2 cloning vector (Fermentas) and sequenced (ABI Prism 3130xl DNA sequencer).

Results and discussion

Prediction of potential V. unguiculata miRNAs and their precursors (pre-miRNAs)

A total of 18 mature, conserved V. unguiculata miRNAs were identified from 2,41,606 V. unguiculata EST (15) and GSS (3) sequences (Table 1) through gene homology search followed by a set of strict filtering criteria including secondary structure analysis using MFOLD 3.2. Of these 18 V. unguiculata miRNAs, 12 (67%) were found to be located at the 3′ arm, while the rest (33%) were in 5′ of the hairpin pre-miRNA sequences as shown in Fig. 2. All the miRNAs classified into 16 miRNA families (miR156, 157, 159, 160, 162, 164, 168, 169, 172, 319, 395, 399, 408, 482, 1507 and 2118). All families are represented by a single member, except miR399 (vun-miR399b, c) and miR1507 (vun-miR1507a, b) represented by two members. All the miRNAs identified in this study were reported first time in V. unguiculata except vun-miR1507a and 1507b; these two were computationally predicted and reported previously by Wang et al. (2009). The length of identified miRNA precursors varied from 72 to 223 nt with an average of 121.5 ± 49.03 and with a median of 106 nt. More than 80% of pre-miRNAs are between 70 and 160 nt, similar to what has been observed in A. thaliana, O. sativa and Glycine max (Li et al. 2005; Zhang et al. 2008a, b; Table 1). The different sizes of the identified miRNAs suggest unique functions in the regulation of miRNA biogenesis or gene expression (Zhang et al. 2006d). The V. unguiculata pre-miRNAs have low and negative MFEs, with an average of about −52.2 kcal/mol ± 16.13, which indicates a higher stability and represents good agreement with previous reports of plant miRNA identification (Yin et al. 2008; Zhang et al. 2008a, b); the A + U content of the pre-miRNAs also ranged from 40.80 to 59.26% which is within the valid range (Zhang et al. 2008a, b; Table 1). Fifteen mature V. unguiculata miRNA sequences identified in this study were completely matched with their corresponding homologs; while the rest differed by 1 to 3 nucleotides. The MFEI is also a useful criterion for distinguishing miRNAs from other types of coding or non-coding RNAs. In our results, the identified pre-miRNAs had a high MFEI (0.68–1.18) with an average of about 0.97 ± 0.12; thus ruling out the possibility of being tRNAs, rRNAs or mRNAs with much lower values 0.64, 0.59 and 0.62–0.66, respectively (Zhang et al. 2006c; Table 1). All the mature miRNA sequences are in the stem portion of the hairpin structures, as shown in Fig. 2.
Table 1

Identified conserved miRNAs in Vigna unguiculata

Conserved miRNAs

LM(nt)a

Query miRNAs

miRNA sequences

Accessions

Source

Location

NM(nt)b

LP(nt)c

A + U (%)

MFEs(ΔG)

MFEIs

vun-miR156a

20

ath-miR156a

UGACAGAAGAGAGUGAGCAC

FG899472

EST

5′

0

94

55.32

−41.90

0.99

vun-miR157b

21

ath-miR157b

UUGACAGAAGAUAGAGAGCAC

FG864653

EST

5′

0

126

55.56

−56.30

1.00

vun-miR159b

21

gma-miR159b

CUUGGACUGAAGGGAGCUCCU

FF402397

EST

3′

3

188

59.04

−78.80

1.03

vun-miR160a

21

ath-miR160a

UGCCUGGCUCCCUGUAUGCCA

FG896300

EST

5′

0

117

53.85

−49.20

0.91

vun-miR162a

21

ath-miR162a

UCGAUAAACCUCUGCAUCCAG

FG857345

EST

3′

0

121

50.41

−48.30

0.80

vun-miR164a

21

ath-miR164a

UGGAGAAGGGGAGCACGUGCA

EI899000

GSS

5′

3

72

41.67

−37.20

0.88

vun-miR168a

21

ath-miR168a

UCGCUUGGUGCAGGUCGGGAA

FF543076

EST

5′

0

125

40.80

−63.20

0.85

vun-miR169b

21

ath-miR169b

CAGCCAAGGAUGACUUGCCGG

FG885738

EST

5′

0

110

50.00

−52.80

0.96

vun-miR172b

21

ath-miR172b

AGAAUCUUGAUGAUGCUGCAU

FG809471

EST

3′

0

140

57.14

−61.50

1.02

vun-miR319a

21

ath-miR319a

UUGGACUGAAGGGAGCUCCCU

FF545817

EST

3′

0

223

57.85

−95.00

1.01

vun-miR395a

21

ath-miR395a

CUGAAGUGUUUGGGGGAACUC

EI916205

GSS

3′

0

81

59.26

−37.80

1.14

vun-miR399b

21

ath-miR399b

UGCCAAAGGAGAGUUGCCCUG

FF542107

EST

3′

0

83

56.63

−38.80

1.07

vun-miR399c

21

ath-miR399c

UGCCAAAGGAGAAUUGCCCUG

FF537540

EST

3′

1

85

54.12

−34.40

0.88

vun-miR408

21

ath-miR408

AUGCACUGCCUCUUCCCUGGC

FF541856

EST

3′

0

243

58.85

−67.10

0.68

vun-miR482

24

gma-miR482

UCUUCCCAAUUCCGCCCAUUCCUA

EI895637

GSS

3′

0

100

59.00

−48.70

1.18

vun-miR1507a

22

gma-miR1507a

UCUCAUUCCAUACAUCGUCUGA

FF398185

EST

3′

0

103

54.37

−43.80

0.93

vun-miR1507b

21

gma-miR1507b

UCUCAUUCCAUACAUCGUCUG

FG936932

EST

3′

0

99

54.55

−49.60

1.10

vun-miR2118

22

pvu-MIR2118

UUGCCGAUUCCACCCAUUCCUA

FG927807

EST

3′

0

78

57.69

−35.20

1.06

aLM length of mature miRNAs; bNM number of mismatch; cLP length of precursor

https://static-content.springer.com/image/art%3A10.1007%2Fs11240-010-9857-7/MediaObjects/11240_2010_9857_Fig2_HTML.gif
Fig. 2

Predicted mature miRNAs of Vignaunguiculata and their precursor sequences with stem-loop structures. The mature miRNAs are in bold letters and highlighted with gray shade

Prediction of potential miRNA targets using bioinformatics tool

The conserved nature of miRNAs in different organisms implied their conserved functions (Zhang et al. 2006a). Fifteen potential target genes were predicted employing all the V. unguiculata mature miRNA sequences as the query in a BLASTn search followed by a set of strict filtering criteria (Table 2). These predicted potential target genes belong to several gene families. All of these were functionally categorized as transcription factors, including squamosa promoter-binding protein (SBP)/squamosa promoter binding protein-like (SPL), TCP family transcription factor, auxin response factor (ARF), CCAAT-binding transcription factor (CBF), nuclear factor Y (NFY), PHAP2B, APETALA2 (AP2) and Basic blue copper proteins/Plantacyanins (Table 2). Schwarz et al. (2008) demonstrated that transcription factors SBP/SPL have crucial role in plant growth, vegetative phase transition and root development and are the main target of miRNA family 156. Whereas, miR160 targets ARF and plays a vital role in auxin signaling pathways and root development (Mallory et al. 2005). Liu et al. (2008) have shown that TCP family transcription factor controls the anther and leaf development and are targeted by miR159. While, CCAAT box is one of the most pervasive elements which, with the aid of CBFs regulates embryo morphogenesis as well as cellular differentiation in plant and CBFs are the key target of miR169 (Gusmaroli et al. 2001). AP2 transcription factors play an important role in floral morphology and flowering time and are potent target of miR172 (Chen 2004). The roles of other target transcription factors are still not very obvious. Dong et al. (2005) reported that Basic blue copper proteins/Plastocyanins, chief target of miR408, which might play a role in anther development and pollination in Arabidopsis. Thus, the predicted miRNA targets in the present study further established the fact that majority of miRNAs are act on transcription factors that regulate plant development and organ formations as also shown by Chen (2005), Mallory and Vaucheret (2006), Jones-Rhoades et al. (2006).
Table 2

Potential targets of identified Vigna unguiculata miRNAs

miRNA

Targeted protein

Target function

Targeted sequence

miRNA:Target pairinga

miR156/157

Squamosa promoter-binding protein (SBP)

Transcription factor

FG823042, TC14963

||||||-||||||||||||, ||||||-||||||||||||

miR159

TCP family transcription factor

Transcription factor

FG926223, TC8824

|||-|–|||||||||||||-, |||-|–|||||||||||||-

miR160

Auxin response factor (ARF)

Transcription factor

TC986, TC5649

-||||||||||||||||||||, -||||||||||||||||||||

miR169

CCAAT-binding transcription factor (CBF)

Transcription factor

TC1493, TC5145

:-|||||-||||||||||||-, :-||-|||||||||||||||-

Nuclear transcription factor Y (NFY)

Transcription factor

TC89

|:|||||-||||||||||||-

miR172

PHAP2B protein

APETALA2 protein (AP2)

Transcription factor

Transcription factor

TC4011

TC11977

-|||||||||||||-||||||

–||||||||||||-||||||

miR408

Basic blue copper protein/Plantacyanin

Transcription factor

TC9874, TC9017, TC16529, TC1781

-:|-||||||||||||||||-, -:|-||||||||||||||||-,

-:|-||||||||||||||||-, ||||||–|||||||||||-|

aWatson–Crick base pairing is indicated by a ‘|’; G:U base pairing by a ‘:’; and ‘-’ indicates a mismatch

Experimental validation of predicted miRNAs in V. unguiculata and measurement of their expression level by quantitative real-time PCR (qRT-PCR)

In order to detect whether predicted V. unguiculata miRNAs were expressed in root or not we have performed PCR, cloning and sequencing using small RNA isolated and purified from the root tissue of hydroponically grown plants. In all PCR reactions, one common antisense primer specific to the adaptor sequence and sense primers specific to each predicted miRNA were used. Seven out of 18 predicted V. unguiculata miRNAs were successfully validated from the root tissue and these are vun-miR156a, vun-miR159b, vun-miR160a, vun-miR162a, vun-miR168a, vun-miR169b and vun-miR408. The reason why rest of the predicted miRNAs failed to amplify is possibly due to their expressions in leaves, stem or other organs instead of root or they may not expressed in root at that certain developmental stage. This is in agreement with previous results reported in Arabidopsis, rice and Medicago, where a number of miRNAs expressed only in certain tissues and cell types, during specific developmental stages and under stress conditions (Lu et al. 2005; Sunkar et al. 2007). To address whether the salt stress has any effect on expression level of these 7 validated V. unguiculata miRNAs in root tissue, quantitative real-time PCR (qRT-PCR) using SYBR Green has been carried out and it was found that all of these miRNAs were up-regulated in the root tissue of salt stressed plants compare to non stressed plants (Fig. 3). The expressions of vun-miR159b, vun-miR160a, vun-miR169b and vun-miR408 were found to be mostly affected by salt stress, while the expressions of others were less affected (Fig. 3). Upregulation of vun-miR156, vun-miR159, vun-miR160, vun-miR162, vun-miR168, vun-miR169 and downregulation of their respective targets such as, SBP/SPL, TCP family transcription factor, ARFs, RNAseIII CAF protein, AGO1 and CBF during salt stress has been reported previously in Arabidopsis and Maize (Liu et al. 2008; Ding et al. 2009). However, we could not predict RNAseIII CAF protein and AGO1 in V. unguiculata. Induction of vun-miR408 and repression of its target have been reported during drought and cold stress in Arabidopsis but not during salt stress (Liu et al. 2008), which is in contrary to the present finding.
https://static-content.springer.com/image/art%3A10.1007%2Fs11240-010-9857-7/MediaObjects/11240_2010_9857_Fig3_HTML.gif
Fig. 3

Quantitative analyses of validated miRNAs in salt stressed Vignaunguiculata root tissues using qRT-PCR. The expression level of each miRNA in mock was set as 1, and that in salt stressed root tissue was quantified relative to it, using comparative Ct method. U6 snRNA was selected as normalization control

It has been assumed that plant development and plant adaptation to stress are two different but closely related processes. During conditions of stress, expression of most plant miRNAs essential for plant development and morphogenesis is altered (Sunkar et al. 2007). These altered levels of miRNAs indirectly inhibit development and morphogenesis by regulating expression patterns of their target genes. Subsequently, this indirectly allows plants to mobilize essential resources toward adaptive responses to stress (Sunkar et al. 2007).

Identification of V. unguiculata miRNA targets with 5′ RLM-RACE

To verify cleavage sites of computationally predicted targets of validated miRNAs, a modified 5′ RLM-RACE was performed using total RNA isolated from salt stress-treated root tissues of V. unguiculata. Presence of miRNA directed cleavage products using primers specific to the target transcripts were checked. Finally, one of the target transcripts, TC986 for vun-miR160, was validated successfully where the cleavage occurred opposite to the 10th position from the 5′ end of the miRNA vun-miR160. This is in accordance with the previous reports in other plant species, where majority of the miRNA-RISC complex cleaved their potential target transcripts specifically at that position (Arenas-Huertero et al. 2009; Chen et al. 2009). The validated target (TC986) of vun-miR160 was classified as transcription factor ARF. In this experiment though several potential target transcripts were computationally predicted, validation of only one target has been possible, that is in agreement with Chen et al. (2009) and Zeng et al. (2009) who also have failed to validate all successfully predicted miRNA targets by RLM-RACE.

In this study, several conserved miRNAs in V. unguiculata were predicted and validated. A detailed study is underway to understand the roles of miRNAs in adaptive responses to salt stress in V. unguiculata.

Acknowledgments

We are thankful to the Director, Bose Institute for providing the lab facilities; we also thank the Department of Biotechnology, India, for the financial assistance (Sanction no. BT/01/COE/06/03), a SRF to AK and a RA to SP.

Copyright information

© Springer Science+Business Media B.V. 2010