Identification of grapevine microRNAs and their targets usinghigh-throughput sequencing and degradome analysis

Vitantonio Pantaleo1,†, Gyorgy Szittya2,†, Simon Moxon3, Laura Miozzi1, Vincent Moulton3, Tamas Dalmay2,* and

Jozsef Burgyan1,*

1Istituto di Virologia Vegetale, Consiglio Nazionale delle Ricerche, Torino, Italy,2School of Biological Sciences, University of East Anglia, Norwich, NR4 7TJ, UK, and3School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK

Received 30 November 2009; revised 7 March 2010; accepted 9 March 2010.*For correspondence (fax +39 011 343 809; e-mail J.Burgyan@ivv.cnr.it; fax +44 1603 592 250; e-mail T.Dalmay@uea.ac.uk).†These authors contributed equally in this work.

SUMMARY

In plants, microRNAs (miRNAs) comprise one of three classes of small RNAs regulating gene expression at the

post-transcriptional level. Many plant miRNAs are conserved, and play a role in development, abiotic stress

responses or pathogen responses. However, some miRNAs have only been found in certain species. Here, we

use deep-sequencing, computational and molecular methods to identify, profile, and describe conserved and

non-conserved miRNAs in four grapevine (Vitis vinifera) tissues. A total of 24 conserved miRNA families were

identified in all four tissues, and 26 known but non-conserved miRNAs were also found. In addition to known

miRNAs, we also found 21 new grapevine-specific miRNAs together with their star strands. We have also

shown that almost all of them originated from single genes. Furthermore, 21 other plausible miRNA candidates

have been described. We have found that many known and new miRNAs showed tissue-specific expression.

Finally, 112 target mRNAs of known and 44 target mRNAs of new grapevine-specific miRNAs were identified by

genomic-scale high-throughput sequencing of miRNA cleaved mRNAs.

Keywords: Vitis vinifera, high-throughput sequencing, miRNAs, target identification, RNA silencing.

INTRODUCTION

Gene expression is regulated at several levels to ensure

normal development and appropriate responses to biotic

and abiotic stresses. One of the post-transcriptional regu-

latory mechanisms relies on endogenous small RNA (sRNA)

molecules that are 21–24 nucleotides (nt) in length (Phillips

et al., 2007). In plants there are different sRNA pathways:

this regulatory layer seems to be more complex than in

animals. There are two main types of sRNAs: microRNAs

(miRNAs) and small interfering RNAs (siRNAs), but the latter

class contains several different types (Brosnan and Voinnet,

2009). One common theme in these pathways is that all

sRNAs are produced from double-stranded RNA (dsRNA),

although the dsRNA is generated by different mechanisms

in each pathway. Members of two gene families are involved

in all sRNA pathways: Dicer-like (DCL) and Argonaute

(AGO). In addition, siRNA biogenesis also requires RNA-

dependent RNA polymerases (RDRs). In the model plant

Arabidopsis thaliana there are four DCLs, 10 AGOs and six

RDRs, and different family members are involved in

different pathways. Similarly to model plants, the coding

sequences of major proteins participating in the RNA

silencing pathways have also been predicted in the Vitis

vinifera genome. Based on thsequence similarity, four DCLs,

six RDRs, but only nine AGOs have been identified (Velasco

et al., 2007). Indeed, as already observed in rice (Oryza

sativa), where four AGO1s are expressed (Wu et al., 2009), it

is now clear that not all plant species have the same number

of family members.

miRNAs are generated from hairpin-structure non-coding

transcripts by DCL1, which cleaves a short (21 bp) duplex

from the stem region (Kurihara and Watanabe, 2004). The

duplex consists of the mature miRNA, which is incorporated

into an AGO1 complex and the miRNA* strand, which is

subsequently degraded. The mature miRNA strand guides

the AGO1 complex (RNA-induced silencing complex; RISC)

to protein-coding RNAs, which are cleaved by AGO1 at a

specific position (opposite to the 10th and 11th nucleotides

of the miRNA) (Mallory et al., 2008). Recent findings have

ª 2010 The Authors 1Journal compilation ª 2010 Blackwell Publishing Ltd

The Plant Journal (2010) doi: 10.1111/j.1365-313X.2010.04208.x

shown that the inhibition of gene expression via transla-

tional arrest by the miRNA-guided AGO complex is more

common in plants than was previously believed (Brodersen

et al., 2008).

Endogenous siRNAs are all produced from long perfect

dsRNAs that are generated by transcription of inverted

repeats or by one of the RDR family members. One class of

siRNAs are produced from TAS genes (trans-acting siRNA

genes) through a multiple-step process. The TAS transcripts

are cleaved by an miRNA (Allen et al., 2005), and one of the

cleaved fragments is turned into dsRNA by RDR6. The

dsRNA is then processed into 21-nt ta-siRNAs (trans-acting

siRNAs) by DCL4 in a phased manner (Peragine et al., 2004;

Vazquez et al., 2004). The phase is therefore initiated by the

position of the miRNA cleavage. ta-siRNAs are incorporated

into AGO1 or AGO7 complexes, and target mRNAs for

cleavage, similarly to miRNAs (Adenot et al., 2006). The

second class of siRNAs, the heterochromatin siRNAs, are

24 nt, and are generated by DCL3 from RDR2-produced

dsRNAs (Lu et al., 2006). Their biogenesis also involves the

plant-specific RNA polymerases IV/V (Herr et al., 2005;

Kanno et al., 2005; Onodera et al., 2005). Heterochromatin

siRNAs target the loci they are generated from, and, in the

case of promoter targeting, can lead to transcriptional gene

silencing through heterochromatin formation. The third

class of siRNAs, natural antisense siRNAs (nat-siRNAs),

consists of two types of sRNAs: the 24-nt primary nat-

siRNAs and the 21-nt secondary nat-siRNAs (Borsani et al.,

2005). The primary nat-siRNA is generated by DCL2 that

cleaves a dsRNA made up from overlapping antisense

mRNAs. This siRNA cleaves one of the mRNAs, which is

then turned into dsRNA by RDR6, and the resulting duplex

is processed into 21-nt secondary nat-siRNAs by DCL1

(Borsani et al., 2005).

Initially, miRNAs were identified by the traditional Sanger

sequencing of relatively small-size cDNA libraries of plant

sRNAs from Arabidopsis, rice and poplar (Populus spp.).

Comparison of miRNAs from these species led to the

conclusion that plant miRNAs are highly conserved (Axtell

and Bartel, 2005). This was supported by observations that

even ferns shared common miRNAs with flowering plants

(Floyd and Bowman, 2004). However, it was also noticed

that a small number of miRNAs were not present in the

genomes of some species, suggesting that they have

evolved more recently (Allen et al., 2004). As non-conserved

miRNAs are often expressed at a lower level than conserved

miRNAs, many of those were not found in small-scale

sequencing projects. However, high-throughput sequencing

technologies allowed the identification of many non-

conserved miRNAs in several species (Rajagopalan et al.,

2006; Fahlgren et al., 2007; Moxon et al., 2008a; Szittya

et al., 2008).

Among the cultivated plant species, V. vinifera is one of

the most emblematic examples of phenotypic–genotypic

correlation. Indeed, an unknown number of different phe-

notypes allow V. vinifera to grow or to be cultivated in

allmost all regions lying between 50�N and 40�S, and up to

3500 m a.s.l. Importantly, grape varieties have been vege-

tatively propagated for several hundreds of years; thus,

these plants may possess unique mechanisms to regulate

gene expression. The exploration of sRNA-based regulatory

networks in grapevine is an important step towards our

better understanding of sRNA-based gene regulation. More-

over, the recent descriptions of grapevine genome sequence

provide a solid support for this effort (Jaillon et al., 2007;

Velasco et al., 2007), although the majority of genes are only

annotated computationally.

Here, we describe the high-throughput sequencing anal-

ysis of sRNAs from a cultivated variety of V. vinifera, Pinot

Noir clone ENTAV115, using the Illumina Solexa platform.

The four sRNA libraries have been prepared from leaves,

tendrils, inflorescences and young fruits from field-

cultivated grapevine plants, and produced more than

2 million unique sequences. The most abundant classes

were represented by 21- and 24-nt-long sRNAs, with an

unexpected majority of the 21 mers, compared with the

24 mers, in any tissue analysed. Most of the conserved

families of miRNAs were represented by at least one miRNA

species. We also identified 21 new grapevine-specific

miRNAs and 21 other plausible candidates. Many of the

conserved and grapevine-specific miRNAs showed a tissue-

specific expression profile either based on the number of

reads or confirmed by northern blot analysis. For miRNA

target identification in grapevine we applied a ‘degradome

sequencing’ approach, which globally identifies the rem-

nants of sRNA-directed target cleavage by sequencing the 5¢ends of uncapped RNAs (Addo-Quaye et al., 2008; German

et al., 2008). We identified a total of 112 target mRNAs as

conserved miRNA targets, and 44 target mRNAs were

confirmed for grapevine-specific miRNAs.

RESULTS

cDNA libraries of endogenous sRNAs

sRNAs with 5¢-phosphate and 3¢-OH (likely to be DCL

products) from V. vinifera Pinot noir clone ENTAV115 were

identified by high-throughput Illumina Solexa sequencing.

cDNA libraries were made from whole young leaves (until

the 3� internodes from the shoot apex; hereafter leaves),

tendrils, whole inflorescences and newly developed small

fruits (ca. 4 mm in size; hereafter berries). These four

cDNA libraries yielded more than 24 million reads. Those

flanked by the 3¢ and 5¢ Solexa adaptors, and with a

minimum and maximum length of 16 and 27 nt, respec-

tively, were compared with the V. vinifera genome. More

than 2 million non-redundant reads were perfectly mat-

ched to at least one locus, and were analysed further

(Table 1).

2 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

The abundance of the 21-nt class of sRNAs is higher than

expected

Previous studies showed that the 24-nt sRNAs are more

abundant in plants than the 21-nt class (Rajagopalan et al.,

2006; Fahlgren et al., 2007; Moxon et al., 2008a). However, in

our four libraries the 21-nt class of sRNAs showed the

highest abundance (Figure 1a–d). As this result was unex-

pected, we compared the number of 21-nt RNAs with that of

the 24-nt RNAs experimentally in different species. The

result presented in Figure 1g shows a nearly equal number

of 21- and 24-nt sRNAs in grapevine leaves, whereas in

A. thaliana, Solanum lycopersicum and Nicotiana benth-

amiana leaves, only the 24-nt sRNAs are detectable by

SYBR-gold staining. We have analogous observations for

tendrils, inflorescences and berries (not shown). These

findings are in line with the sequencing results (Figure 1a–f).

As expected, the 21-nt class showed the highest redun-

dancy because a relatively small number of non-redundant

sequences are expressed at a high level (Figure 1a–f).

Importantly, after removing rRNA/tRNA sequences, the

majority of redundant sequences matching with the grape

genome were miRNAs in all four tissues, which may explain

the high abundance of the 21-nt size class (Table 1). The

24-nt class of sRNAs showed much less redundancy because

many different sequences are generated from each

24-nt-producing locus. The least abundant although clearly

identifiable sRNA size class was the 22-nt class from all

V. vinifera tissues, showing redundancy similar to the 24-nt

class (Figure 1a–f). Expression of the non-redundant 24-nt

sRNAs was slightly higher than the 21-nt class in all tissues,

which was particularly pronounced in the inflorescence

tissue (Figure 1f). The only exception was in tendrils, in

which the frequency of non-redundant 24-nt sRNAs was

slightly lower than the 21-nt size class. In Figure 2 we show

the distribution of non-redundant 24-nt siRNAs within the

whole grapevine genome according to the annotation of

Jaillon et al. (2007). The majority of 24-nt siRNAs map to

intronic regions, a relevant percentage of them map to

intergenic regions, and only a slight percentage are derived

from the coding sequence region and the untranslated

region (UTR). This profile differs from that observed in

A. thaliana, where most siRNAs were predominantly

mapped to intergenic regions (Rajagopalan et al., 2006).

The distribution of 24-nt siRNAs was also identified for each

chromosome (Figure S1). Interestingly, the distributions of

24-nt siRNAs derived from the four different tissues were

very similar.

Table 1 Statistics of short RNA sequences from Vitis vinifera leaves, tendrils, inflorescences and berries

Redundant Non-redundant

ReadsMatching grapegenome Reads

Matching grapegenome

Leaves Raw reads 4.341.229Adaptor removed 3.418.590 231.949Filter by sequence properties 3.389.523 226.987rRNA/tRNA exact matches removed 3.334.333 2.421.606 222.136 92.035Match known miRNAsa 2.276.579 1.701.998 6455 (37) 303 (34)sRNA from predicted hairpins with abundance ‡5 1.711.202 65

Tendrils Raw reads 6.009.306Adaptor removed 4.701.135 583.460Filter by sequence properties 4.700.923 583.274rRNA/tRNA exact matches removed 4.477.386 2.458.385 571.276 205.499Match known miRNAsa 1.555.382 1.245.761 6836 (43) 357 (32)sRNA from predicted hairpins with abundance ‡5 668.756 98

Inflorescences Raw reads 7.089.405Adaptor removed 6.177.776 720.819Filter by sequence properties 6.176.982 720.312rRNA/tRNA exact matches removed 4.763.234 3.252.126 706.442 323.127Match known miRNAsa 1.331.370 1.011.827 8006 (44) 464 (36)sRNA from predicted hairpins with abundance ‡5 796.222 99

Berries Raw reads 6.781.437Adaptor removed 4.854.903 528.868Filter by sequence properties 4.848.444 525.909rRNA/tRNA exact matches removed 3.626.958 2.148.829 513.557 185.923Match known miRNAsa 1.211.565 895.356 9043 (42) 403 (37)sRNA from predicted hairpins with abundance ‡5 783.664 80

aSmall RNAs (sRNAs) matching known mature microRNAs (miRNAs) (miRbase v13) with a maximum of two mismatches; numbers betweenbrackets indicate the number of matching known mature miRNAs.

Grapevine microRNAs and their targets 3

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

Known miRNAs in V. vinifera

Conserved families of miRNAs were found in many plant

species and have important functions in plant development

and stress response (Jones-Rhoades et al., 2006). Indeed,

the recent sequencing of the entire grapevine genome

allowed the prediction of 28 (Jaillon et al., 2007; Velasco

et al., 2007) conserved and known non-conserved miRNAs

families within the grapevine genome, based on similarities.

As expected, we have identified the members of almost all

(24 families) conserved miRNA families in the four cDNA

libraries generated (Table 2). The expression level of a few

miRNA families were similarly high (e.g. miR166) or low (e.g.

miR160 and miR391) in all tissues; however, other conserved

miRNAs showed clear tissue-specific expression, such as,

miR156, miR159, miR164, miR167, miR168 and miR172

(Table 2). Several conserved miRNAs (miR156, miR162,

miR164, miR167, miR171, miR172, miR319, miR393,

miR397 and miR403) were expressed at a higher level in

inflorescences than in tendrils (Table 2). In contrast, miR159

and miR395 were expressed at a higher level in tendrils than

in inflorescences (Table 2). Northern analysis usually agreed

with the sequencing data, as in the cases of miR156, miR162,

miR164, miR167, miR171, miR319, miR393, miR397 and

miR403, which showed clear tissue-specific expression,

similarly to the obtained sequencing data. Although in some

cases we observed a discrepancy between the northern

blot and sequencing data (miR159, miR168 and miR172;

Figure 3; Table 2).

In addition to the conserved miRNAs, there are other

known miRNAs that are not conserved, but were found in

only one or a few plant species (Jones-Rhoades et al., 2006).

Several non-conserved miRNAs (26 families) were also

present in our data sets at a low abundance, with the

exception of miR827 that was represented by a high read

number (Table 2). Few non-conserved miRNAs have shown

different expression levels in the four tissues. The frequency

of miR479 and miR529 reads was more abundant in tendrils

than in inflorescences. In contrast, miR482, miR858 and

miR894 were expressed at a higher level in inflorescences

than in tendrils (Table 2). We also confirmed the sequencing

results by northern blot analysis for selected non-conserved

miRNA species (Figure 3). Similarly to conserved miRNAs,

the relative readings of known miRNAs in the cDNA libraries

were in line with the northern blot profiles. Interestingly, we

have identified four non-conserved miRNAs (miR443,

(a)

(c)

(g)

(b) (e)

(f)

(d)

Figure 1. Size distribution of redundant and non-redundant short RNA sequences.

Number of redundant and non-redundant short RNA (sRNA) sequences from leaves, tendrils, inflorescences and berries are shown in panels (a–d), respectively. Size

distribution of redundant and non-redundant sRNAs in leaves, tendrils, inflorescences and berries are shown in panels (e and f), respectively. Vitis vinifera sRNAs

compared with sRNAs from other plant species and visualized with SYBR-gold staining (g). The frequency is expressed as a percentage of the total number of

sequences for each organ for (e) and (f).

4 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

miR1432, miR1858 and miR1859) previously found only in

the monocotyledon O. sativa.

We also searched the grapevine sRNAs for longer miRNA

species potentially generated by DCL3 (Vazquez et al., 2008).

We found the longer version (23–24 nt) of 15 miRNA species

belonging to 10 different miRNA families. Among them, only

miR166, miR479, miR535a and miR828a showed a consid-

erable percentage of long size versions (23–24 nt), ranging

from 1.2 to 14.3% of the total reads (Table S1).

Grapevine-specific miRNAs

The sRNA reads were mapped to the V. vinifera genome

(http://www.genoscope.cns.fr/spip/Vitis-vinifera-whole-

genome.html), and secondary structures were predicted for

each locus. Based on the hairpin prediction, we selected 42

miRNA candidates that were potentially generated from 60

loci (Figure S2). Furthermore, we found the miRNA* strands

for 21 out of the 42 new miRNA candidates that are poten-

tially produced from 26 loci (Table 3). Most new miRNAs can

only be produced from one locus, except miRC8 and

miRC11, which could be produced from three and four loci,

respectively.

In grapevine, none of the conserved MIR genes were

found close to each other on the chromosomes; however,

we found one cluster containing grapevine-specific miRNAs.

Precursors of miRC13 and miRC15 are spaced 224-bp apart

on chromosome 17, oriented in the same direction (Fig-

ure 4a and b). Although these two miRNA precursors are

located quite close to each other, we don’t know whether

they derived from one or two transcripts. MiRC13 is

expressed at low levels whereas miRC15 is expressed at

high levels in inflorescences and berries, respectively (Fig-

ure 5b). This finding may suggest that they are derived from

different transcripts, or that they are differently processed in

different tissues.

Some of the grapevine-specific miRNAs were abundant in

specific tissues, and most of them showed differential

expression in the four tissues analyzed (Figure 5a). The

relative number of reads in all tissues was very low for

miRC4, miRC5, miRC6 miRC7, miRC8a-c, miRC9, miRC10,

miRC11a-d, miRC12 and miRC19. This trend was confirmed

by northern blot analysis because we obtained no or very

weak signal for these miRNAs, except for miRC12. This new

miRNA gave a very strong signal in leaves, inflorescences

and berries, which was not expected from the sequencing

data (Figure 5b). The expression profiles obtained by north-

ern blot analysis were different from the sequencing data for

miRC1, miR13 and miRC15. However, for the other new

miRNAs (miRC2, miRC3, miRC14, miR16, miRC17, miRC18,

miRC20 and miR21), sequencing data and northern blot

analysis showed good correlation (Figures 5a and 4b).

Inflorescences and tendrils showed different patterns for

many new miRNAs, similar to the conserved miRNAs.

Several new miRNAs (miRC2, miRC3, miR7, miR11, miRC12,

miR14, miRC15, miR16, miRC17 and miRC20) accumulated

at a higher level in inflorescences than in tendrils. In

contrast, miRC6 showed the opposite pattern, although only

on the northern blot (Figure 5b).

Targets of known miRNAs

To generate a miRNA cleaved target library (degradome)

from grapevine we applied a recently developed high-

throughput experimental approach that can identify mRNAs

targeted by sRNAs (Addo-Quaye et al., 2008; German et al.,

2008). The poly-A fraction of total RNA extracted from young

leaf tissue was analysed for the identification of target

transcripts of known and new miRNAs.

We obtained a total number of 7 761 210 short sequenc-

ing reads representing the 5¢ ends of uncapped, poly-

adenylated RNAs. After initial processing, equal numbers

of 20- and 21-nt sequence reads were obtained, and 56.8% of

the unique signatures could be mapped to the V. vinifera

transcriptome.

Previous studies established that the 5¢ ends of miRNA-

cleaved mRNA fragments would correspond to the nucleo-

tide that is complementary to the 10th nucleotide of the

miRNA. Therefore, the cleaved RNA targets should have

distinct peaks in the degradome sequence tags at the

predicted cleavage site relative to other regions of the

transcript (Addo-Quaye et al., 2008; German et al., 2008).

However, previous studies have shown that in some

cases neighboring nucleotides (the ninth or eleventh

positions) were also identified as cleavage sites for some

plant miRNAs. This observation accounts for the occa-

sional positional heterogeneity seen for mature miRNAs

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%Intergenic Intron UTR CDS

Leaf Inflore-scence

Tendril Berry Genome

Figure 2. Origin of non-redundant 24-nt small interfering RNAs (siRNAs)

referred to the genomic annotation. The first four bars refer to the distribution

of 24-nt siRNAs found in each data set, whereas the last bar refers to the

percentage of genomic regions within the Vitis vinifera genome, according to

Jaillon et al. (2007).

Grapevine microRNAs and their targets 5

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

Table 2 Known microRNAs (miRNAs) in grapevine

miRNA family References

Relative number of reads found in Vitis viniferaa

Leaves Tendrils Inflorescences Berries

Conserved miRNAsmiR156 Jones-Rhoades et al., 2006 61.38 100.93 886.2 288.24miR159 Jones-Rhoades et al., 2006 7105.8 158 000.0 48 300.0 47 200.0miR160 Jones-Rhoades et al., 2006 0.6 0.23 2.18 4.08miR162 Jones-Rhoades et al., 2006 184.8 255.9 747.0 568.6miR164 Jones-Rhoades et al., 2006 9670.38 1357.83 15 600 37 100miR165 Rajagopalan et al., 2006 5586.93 2458.9 2193.82 4105.02miR166 Jones-Rhoades et al., 2006 635 000.0 185 000.0 204 000.0 240 000.0miR167 Jones-Rhoades et al., 2006 20 100 90.45 4368.25 13600miR168 Jones-Rhoades et al., 2006 430.9 928.6 646.4 2724.2miR169 Jones-Rhoades et al., 2006 2.72 10.02 20.69 12.24miR171 Jones-Rhoades et al., 2006 12.7 11.2 99.3 58.9miR172 Jones-Rhoades et al., 2006 26.61 26.88 2682.33 590.76miR319 Jones-Rhoades et al., 2006 97.7 1447.4 2882.7 1862.6miR390 Jones-Rhoades et al., 2006 106.14 190.69 285.31 196.14miR391 Jones-Rhoades et al., 2006 0.3 0.0 0.2 0.9miR393 Jones-Rhoades et al., 2006 0.91 1.14 42.47 11.37miR394 Jones-Rhoades et al., 2006 1.8 0.5 0.4 3.2miR395 Jones-Rhoades et al., 2006 38.71 398.69 3.27 10.2miR396 Jones-Rhoades et al., 2006 165.4 662.3 753.6 864.4miR397 Jones-Rhoades et al., 2006 5.44 12.3 63.6 20.11miR398 Jones-Rhoades et al., 2006 0.0 0.0 1.3 1.2miR399 Jones-Rhoades et al., 2006 0.6 0.68 1.31 0.58miR403 Jones-Rhoades et al., 2006 523.1 192.1 800.6 265.8miR408 Jones-Rhoades et al., 2006 0.6 0 0.65 0.58

Other known miRNAsmiR170 Rajagopalan et al., 2006; Moxon et al., 2008a 0 0 0.22 0miR418 Jones-Rhoades et al., 2006 0.0 0.2 0.0 0.0miR443 Sunkar et al., 2005 0.3 0 0 0miR472 Lu et al., 2006; Moxon et al., 2008a,b 0.0 0.2 0.0 0.6miR477 Axtell et al., 2007 0 0.23 0 0miR479 Lu et al., 2005 1.8 91.4 33.3 65.6miR482 Lu et al., 2005; Moxon et al., 2008a,b 0.91 17.31 46.83 55.37miR529 Liu et al., 2005; Axtell et al., 2007 134.3 139.0 4.4 1.8miR530 Lu et al., 2008; Liu et al., 2005 0 0 0.44 0.58miR535 Arazi et al., 2005 25.7 89.1 83.9 65.3miR827 Lacombe et al., 2008 7904.43 1943.56 1795.26 2215.28miR828 Rajagopalan et al., 2006; Moxon et al., 2008a,b 0.6 0.7 5.4 0.9miR858 Fahlgren et al., 2007; Moxon et al., 2008a,b 1.21 1.59 27.88 7.87miR894 Fattash et al., 2007; Moxon et al., 2008a,b 23.0 20.7 55.3 30.0miR896 Fattash et al., 2007 0 0.23 0.65 0.87miR902 Fattash et al., 2007 0.0 0.2 0.0 0.0miR1030 Axtell et al., 2007 0 0 0.22 0miR1091 Axtell et al., 2007 0.0 0.2 0.0 0.0miR1103 Axtell et al., 2007 0 0.23 0 0miR1124 Yao et al., 2007 0.0 0.7 0.2 0.0miR1134 Yao et al., 2007 0 0.68 0.22 0miR1432 Lu et al., 2008 0.0 0.2 0.0 0.0miR1507 Subramanian et al., 2008;

Szittya et al., 2008; Wang et al., 20098.47 6.83 6.53 5.54

miR1511 Subramanian et al., 2008 0.0 0.2 0.2 1.2miR1858 Zhu et al., 2008 0 0 0.22 0.29miR1859 Zhu et al., 2008 0.0 0.0 0.2 0.0

aThe relative number of reads was obtained by dividing the number of reads of each microRNA (miRNA) with the total number of reads of eachcDNA library. Reads encompass the defined miRNA sequence � 2 nt on either side.

6 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

(Rajagopalan et al., 2006) and their cleavage products

(Jones-Rhoades and Bartel, 2004; Fahlgren et al., 2007). In

our analysis we have applied the recently described CLEAVE-

LAND pipeline (Addo-Quaye et al., 2008, 2009) to identify

cleaved targets for both known and new miRNAs in grape-

vine. Abundance of the sequenced tags was plotted on each

transcript, and the result shown on Figures S3 and S4 and

the cleaved target transcripts have been categorized into

three classes (categories I, II and III), as reported previously

for Arabidopsis (Addo-Quaye et al., 2008, 2009).

For known (conserved and non-conserved) miRNAs we

identified a total of 112 target mRNAs (Table S2). Among the

112 grapevine miRNA targets, the signatures associated

with the conserved miRNA targets are the most abundantly

represented. A total of 76 targets were found for conserved

miRNAs, from which 29 were classed as category I. For non-

conserved miRNAs we have found 36 targets, from which

five were classed as category I. Category-I targets are

transcripts where the degradome tags corresponding to

the expected miRNA-mediated cleavage site were the most

abundant tags matching the transcript. Target transcripts fall

into category II (10 targets including conserved and non-

conserved miRNA targets), where the total abundance of

degradome sequences at the cleavage site is in the top one-

third, but not the maximum. Among the identified targets

the most abundant category was category III (68 targets

including conserved and non-conserved miRNA targets),

where any mRNAs detected with the expected cleavage

signature, and that are neither in category I nor II, are

classed (Figure 6; Table S2).

We identified targets for 13 conserved miRNA families out

of 24. Most of the conserved miRNAs without any identified

targets (miR160, miR391, miR393, miR394, miR398, miR399

and miR408) were expressed at a very low level in leaves

(Table 2), which may explain the absence of cleaved targets.

However, in a few cases the miRNAs (miR168, miR395,

miR396 and miR403) were expressed at a considerable level

(Figure 3; Table 2) without the targets identified in the

degradome library. We have confirmed 24 conserved targets

of conserved miRNAs already identified in Arabidopsis and

eight predicted in grapevine. Most of the identified con-

served targets are members of different families of tran-

scription factors, such as the squamosa promoter binding

(SPB), MYB, TCP, AUXIN response factor and NAC (Table

S2), which have been predicted previously based on in silico

studies (Velasco et al., 2007). In addition to these targets we

also identified 44 new targets in grapevine for conserved

miRNAs (Table S2). With the exception of miR390, all

identified conserved miRNAs had multiple targets, and

those targets were often classified in different classes. The

conserved targets of conserved miRNAs had a high fre-

quency in the sequenced target library, and were often

classified into the class-I category (Figures 6 and S3). For

example, miR172 targets two different ap2-domain-contain-

ing transcription factors (class-I targets) with a very high

frequency (57 and 58%) of cleavage at the expected cleavage

miR166

miR159

miR162

miR167

miR169

miR164

miR156

miR168

U6

U6

U6

U6

U6

U6

U6

L B

miR319

miR390

miR395

miR393

miR397

miR172

miR396

miR171

U6

U6

U6

U6

U6

U6

L B

miR827

miR535

miR403

miR482

miR529

miR858

U6

miR479

U6

U6

U6

U6

U6

L T I T I T I BFigure 3. Expression of selected known micro-

RNAs (miRNAs) in different Vitis vinifera tissues.

Total RNA from different tissues was extracted,

separated and transferred to nylon membranes.

Oligonucleotide probes were used to detect

specific miRNAs, whereas U6-specific probe

was used to detect U6 RNA as a loading control

for each membrane. Key: L, leaves; T, tendrils; I,

inflorescences; B, berries.

Grapevine microRNAs and their targets 7

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

Tab

le3

New

gra

pev

ine

mic

roR

NA

s(m

iRN

As)

and

pu

tati

vem

iRN

As

miR

NA

Ch

rom

oso

me

Sta

rtE

nd

Ori

enta

tio

nG

eno

mic

loca

tio

n(a

)A

bu

nd

ance

Seq

uen

ce(5

¢fi

3¢)

Len

gth

(nt)

Seq

uen

ceo

fcl

on

edp

uta

tive

miR

NA

*(5

¢fi

3¢)

miR

C1

chr1

8_ra

nd

om

523

744

15

237

462

+I

1357

7T

GG

TG

CT

TG

GA

CG

AA

TT

TG

CT

A22

TC

AC

AA

GT

TC

AT

CC

AA

GC

AC

CA

(661

)C

AC

AA

GT

TC

AT

CC

AA

GC

AC

CA

T(4

)A

CA

AG

TT

CA

TC

CA

AG

CA

CC

AT

C(1

4)m

iRC

2ch

rUn

_ran

do

m97

109

145

9710

916

5)

IG30

78T

TC

CA

TC

TC

TT

GC

AC

AC

TG

GA

21T

TG

GT

GT

GC

AC

GG

GA

TG

GA

A(1

)T

GG

TG

TG

CA

CG

GG

AT

GG

AA

TA

(160

)T

GG

TG

TG

CA

CG

GG

AT

GG

AA

TA

C(3

)T

GG

TG

TG

CA

CG

GG

AT

GG

AA

T(6

)G

GT

GT

GC

AC

GG

GA

TG

GA

AT

AC

(23)

GG

TG

TG

CA

CG

GG

AT

GG

AA

TA

C(2

3)G

GT

GT

GC

AC

GG

GA

TG

GA

AT

A(1

1)m

iRC

3ch

r82

153

996

215

401

6+

I64

6T

CA

GG

GC

AG

CA

GC

AT

AC

TA

CT

21T

AG

TA

TG

CT

GC

TG

TC

TT

TA

GA

(1)

miR

C4

chr1

72

382

965

238

298

5)

IG51

CG

GG

AG

AT

GA

CT

AC

TG

GA

AG

C21

TT

CC

AG

CA

GT

CA

TC

TC

CA

AG

G(1

)m

iRC

5ch

r817

351

755

1735

177

5+

CD

S/I

41G

GT

AG

TC

GC

TG

TG

AA

AT

TG

AA

21C

TT

CA

AT

TT

CA

CA

GC

GA

CC

AC

(4)

CA

AT

TT

CA

CA

GC

GA

CC

AC

TG

G(2

)A

AT

TT

CA

CA

GC

GA

CC

AC

TG

GT

(1)

AA

TT

TC

AC

AG

CG

AC

CA

CT

GG

T(1

)m

iRC

6ch

r14

1749

278

717

492

808

)IG

38T

TG

TC

GC

AG

GA

GA

GA

CG

GC

AC

T22

TC

GC

CG

CT

CT

CC

TG

TG

AC

AA

G(1

)m

iRC

7ch

rUn

_ran

do

m12

532

758

112

532

760

1+

IG35

CT

AA

GC

AC

AG

CT

CT

CG

CA

TC

C21

AT

GC

GA

GA

GC

CG

TG

CT

TA

GT

A(1

)m

iRC

8_1

chr1

310

690

055

1069

007

5)

I7

GG

CT

GC

TG

AG

AA

AA

TG

TA

GG

A21

CG

CA

TT

TT

CT

CA

GC

AG

CC

AA

G(1

)m

iRC

8_2

chr1

43

088

473

308

849

3)

UT

R7

GG

CT

GC

TG

AG

AA

AA

TG

TA

GG

A21

NO

miR

C8_

3ch

r17

810

757

810

777

+IG

7G

GC

TG

CT

GA

GA

AA

AT

GT

AG

GA

21N

Om

iRC

9ch

r21

044

027

104

404

8+

IG5

AC

TC

TT

TC

TC

AA

GG

GC

TT

CT

AG

22C

GA

AG

TC

TT

TG

GG

GA

GA

GT

GG

(4)

miR

C10

chr1

77

012

577

701

259

7+

IG5

TG

CA

AG

TG

AC

GA

TA

TC

AG

AC

A21

TT

TG

GG

AA

TC

TC

TC

TG

AT

GC

AC

(1)

miR

C11

_1ch

r12_

ran

do

m2

088

393

208

841

4+

I21

CA

TG

TT

GA

CA

TC

AT

CC

AA

TA

TA

22T

AT

AT

TG

GA

TG

AT

GT

CA

AC

AA

(1)

miR

C11

_2ch

r56

289

272

628

929

3+

IG21

CA

TG

TT

GA

CA

TC

AT

CC

AA

TA

TA

22T

AT

GT

TG

GA

TG

AT

GT

CA

AT

AA

(1)

AT

GT

TG

GA

TG

AT

GT

CA

AT

AA

G(1

)T

GT

TG

GA

TG

AT

GT

CA

AT

AA

GT

T(2

)T

GT

TG

GA

TG

AT

GT

CA

AT

AA

GT

(4)

miR

C11

_3ch

rUn

_ran

do

m94

833

716

9483

373

7)

IG21

CA

TG

TT

GA

CA

TC

AT

CC

AA

TA

TA

22N

Om

iRC

11_4

chr1

73

462

693

346

271

4)

IG21

CA

TG

TT

GA

CA

TC

AT

CC

AA

TA

TA

22N

Om

iRC

12ch

r14

1259

340

712

593

428

+IG

35T

TT

CC

CA

GA

CC

CC

CA

AT

AC

CA

A22

GG

AT

TG

GG

GG

CC

GA

TG

GA

AA

GG

(6)

miR

C13

chr1

75

578

290

557

830

9+

IG28

92G

GA

AT

GG

AT

GG

TT

AG

GA

GA

G20

TT

CC

TA

TA

CC

AC

CC

AT

TC

CC

TA

(97)

GT

TC

CT

AT

AC

CA

CC

CA

TT

CC

CT

A(1

6)T

TC

CT

AT

AC

CA

CC

CA

TT

CC

CT

(5)

miR

C14

chr1

75

737

903

573

792

5–

I16

6T

TT

CC

GA

CT

CG

CA

CT

CA

TG

CC

GT

23G

GC

AT

AT

GT

GT

GA

CG

GA

AA

GA

(49)

miR

C15

chr1

75

577

934

557

795

4+

IG12

38G

GA

AT

GG

GT

GG

CT

GG

GA

TC

TA

21G

TT

CC

CA

TG

CC

AT

CC

AT

TC

CT

A(8

8)m

iRC

16ch

r18

1786

179

517

861

815

)IG

8114

GG

CA

TG

TG

TG

GG

GC

AT

AA

TA

G21

AT

TA

TG

TC

CC

AC

AC

AT

GC

CT

C(3

89)

miR

C17

chr1

64

228

390

422

841

3)

IG20

252

GT

CT

GT

CG

GA

GA

AG

CA

AG

TC

GG

AG

24T

CG

GT

TT

GC

TT

CT

TT

GA

TA

GA

TT

C(1

)m

iRC

18ch

r16

677

916

66

779

189

)I

696

TT

TC

GA

CA

AG

AC

AC

AA

TG

CA

TA

AA

24A

TT

TA

TG

TA

TT

GT

GT

TT

TG

TC

GG

A(1

6)

TA

TG

TA

TT

GT

GT

TT

TG

TC

GG

AA

AA

(1)

miR

C19

chr1

77

216

848

721

687

1)

I20

GC

AA

CA

AG

CA

TG

AA

AA

GG

CA

CA

CC

24T

GT

GC

CT

TT

TC

GC

GC

TT

GT

TG

CT

A(2

)m

iRC

20ch

r915

466

659

1546

668

2+

I20

08A

TT

GA

CT

TC

TG

AA

AG

GC

TA

AA

AG

C24

GA

GC

TT

TT

GG

CT

TC

TC

AG

AA

GT

CA

(3)

miR

C21

chrU

n_r

and

om

114

581

158

114

581

181

)I

1249

AT

CG

AA

AA

GG

CA

TC

AT

CA

AT

CA

GG

24A

CC

TG

AT

TG

GT

GA

TG

CT

TT

TT

TG

G(6

)

8 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

Tab

le3

(Co

nti

nu

ed)

miR

NA

Ch

rom

oso

me

Sta

rtE

nd

Ori

enta

tio

nG

eno

mic

loca

tio

n(a

)A

bu

nd

ance

Seq

uen

ce(5

¢fi

3¢)

Len

gth

(nt)

Seq

uen

ceo

fcl

on

edp

uta

tive

miR

NA

*(5

¢fi

3¢)

miR

C22

chr5

666

049

86

660

519

)IG

7788

2T

TA

CA

CA

GA

GA

GA

TG

AC

GG

TG

G22

NO

miR

C23

chr1

417

809

225

1780

924

6+

IG53

6T

CT

GT

CG

CA

GG

AG

AG

AT

GA

TG

C22

NO

miR

C24

_1ch

r17

598

477

65

984

797

+IG

478

TC

CC

AG

GA

GA

GA

TG

GC

AC

CT

GC

22N

Om

iRC

24_2

chr1

75

985

000

598

502

1+

IG47

8T

CC

CA

GG

AG

AG

AT

GG

CA

CC

TG

C22

NO

miR

C25

_1ch

rUn

_ran

do

m14

601

027

714

601

029

7–

CD

S/I

134

AA

CT

GT

GG

CT

TT

GA

CG

GT

GT

A21

NO

miR

C25

_2ch

r13

1115

013

711

150

157

+C

DS

/I13

4A

AC

TG

TG

GC

TT

TG

AC

GG

TG

TA

21N

Om

iRC

26ch

r64

462

454

446

247

4+

IG66

TC

AA

AA

GA

GA

AA

AT

GT

GG

AT

G21

NO

miR

C27

chr1

_ran

do

m2

541

779

254

179

9)

IG28

TT

TG

AG

AG

GA

AG

AG

GA

AG

AA

A21

NO

miR

C28

_1ch

r14_

ran

do

m1

026

601

102

662

1+

I19

AA

TG

CT

AG

AA

AC

AC

TT

CT

CA

A21

NO

miR

C28

_2ch

rUn

_ran

do

m50

911

499

5091

151

9)

IG19

AA

TG

CT

AG

AA

AC

AC

TT

CT

CA

A21

NO

miR

C28

_3ch

r45

011

252

501

127

2)

IG19

AA

TG

CT

AG

AA

AC

AC

TT

CT

CA

A21

NO

miR

C29

chrU

n_r

and

om

8902

952

489

029

544

)I

12G

AG

AT

AA

GA

AG

GC

GA

TG

GT

AT

21N

Om

iRC

30_1

chrU

n_r

and

om

1601

864

016

018

660

+I

8C

TA

GG

AA

GC

GC

TT

TT

AA

TA

TT

21N

Om

iRC

30_2

chrU

n_r

and

om

9192

734

991

927

369

)I

8C

TA

GG

AA

GC

GC

TT

TT

AA

TA

TT

21N

Om

iRC

30_3

chr1

314

203

931

1420

395

1)

IG8

CT

AG

GA

AG

CG

CT

TT

TA

AT

AT

T21

NO

miR

C30

_4ch

r14

1771

148

517

711

505

+I

8C

TA

GG

AA

GC

GC

TT

TT

AA

TA

TT

21N

Om

iRC

30_5

chr6

878

537

08

785

390

+IG

8C

TA

GG

AA

GC

GC

TT

TT

AA

TA

TT

21N

Om

iRC

30_6

chr1

28

625

266

862

528

6)

I8

CT

AG

GA

AG

CG

CT

TT

TA

AT

AT

T21

NO

miR

C30

_7ch

r23

066

240

306

626

0+

I8

CT

AG

GA

AG

CG

CT

TT

TA

AT

AT

T21

NO

miR

C30

_8ch

r11

1174

879

411

748

814

+I

8C

TA

GG

AA

GC

GC

TT

TT

AA

TA

TT

21N

Om

iRC

30_9

chr1

054

133

354

135

3)

I8

CT

AG

GA

AG

CG

CT

TT

TA

AT

AT

T21

NO

miR

C30

_10

chr1

0_ra

nd

om

279

095

279

115

)I

8C

TA

GG

AA

GC

GC

TT

TT

AA

TA

TT

21N

Om

iRC

31ch

rUn

_ran

do

m54

330

633

5433

065

3)

IG20

CC

TA

AA

GA

GC

AT

GA

TA

TG

TA

C21

NO

miR

C32

chr1

217

274

532

1727

455

2)

I14

AG

AA

GA

AC

AA

GT

AG

AC

TG

AG

C21

NO

miR

C33

chr8

1122

314

211

223

162

)I

14G

TA

GA

TT

AA

GA

GG

AG

GG

GG

AC

21N

Om

iRC

34ch

r16

973

069

697

308

9+

I7

AA

TC

TG

AG

AC

CC

TT

TT

TT

TG

A21

NO

miR

C35

chr7

464

140

74

641

428

+IG

7A

GT

GT

GC

GG

AG

AA

GC

AA

AA

CG

G22

NO

miR

C36

chr6

933

211

39

332

133

)IG

7C

AT

GA

CA

AA

AG

AT

AC

TT

CA

TT

21N

Om

iRC

37ch

r15

856

806

585

682

5)

IG7

GG

AG

AC

CT

GA

AC

TG

AA

GA

GC

20N

Om

iRC

38ch

r814

329

557

1432

957

7)

IG7

TA

AT

CT

GC

AT

CC

TG

AG

GT

CT

A21

NO

miR

C39

chr4

114

304

51

143

065

)I

5A

CA

GT

AG

GA

AA

TT

GA

AA

GA

GA

21N

Om

iRC

40ch

r46

511

949

651

196

9+

IG5

AT

TA

AT

TG

TT

CC

CA

CC

GC

TC

T21

NO

miR

C41

chr7

499

312

54

993

145

)I

5T

GG

TT

CA

GA

AA

TG

CA

TA

GG

AC

21N

Om

iRC

42ch

rUn

_ran

do

m34

389

288

3438

930

9)

CD

S38

TG

CA

GA

GG

AA

GG

AG

GA

AG

AG

GA

22N

O

Grapevine microRNAs and their targets 9

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

site, but it also guides the slicing of other targets previously

not identified in other plants with very low frequency.

Similarly, four members of the SBP gene family were

targeted by miR156 with high frequency, whereas other

non-conserved targets of miR156 were identified with low

frequency (Table S2).

We found a total of 33 target genes for eight known non-

conserved miRNA families out of 26. Three targets of

miR858 (two members of the MYB transcription family and

one unidentified protein gene) were already identified in

Arabidopsis; the other 30 are new targets of these non-

conserved miRNAs. These targets were cleaved with sub-

stantially lower frequency than the targets of conserved

miRNAs. However, four members of the MYB transcription

factor family were targeted with high frequency by miR828

and classified into category I (three members) or II (one

member) (Figure S3; Table S2). Those non-conserved

miRNA families for which no target had been identified

were not present in leaf tissue (miR170, miR418, miR472,

miR477, miR530, miR896, miR902, miR1030, miR1091,

miR1103, miR1124, miR1134, miR1432, miR1511, miR1858

and miR1859), except in miR443 (expressed at a very low

level) and miR529 (Table 2).

Interestingly, we identified target transcripts that were

regulated by pairs of miRNAs: miR156 and miR535 target

three members of the same SBP family, the pair of miR159/

miR319 controls two transcription factors, and the miR165/

miR166 pair targets six different targets, suggesting a

combinatorial regulation of these genes by the indicated

miRNA pairs (Figure S3; Table S2).

Grapevine-specific miRNA targets

Out of the 21 new miRNAs with star strands, we only iden-

tified targets for eight miRNAs (miRC2, miRC3, miRC5,

miRC9, miRC11, miRC12, miRC13 and miRC16) (Table 4). In

addition, targets were identified for three new miRNA

(a)

(b)

Figure 4. Cluster of new microRNAs (miRNAs).

Schematic representation of the cluster contain-

ing miRC13 and miRC15 is shown in panel (a).

Suggested primary transcript containing miRC13

and miRC15. Blue boxes represent the predicted

stem-loop structures. For miR15, red and purple

represent the mature miRNAs and miRNAs*,

respectively. For miR13, dark blue and light

green represent the mature miRNAs and

miRNAs*, respectively.

10 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

candidates (without sequenced star strands): miRC23,

miRC25 and miRC26 (Table 4). The abundance of the

sequence tags for grapevine-specific miRNA target tran-

scripts were plotted as a function of its position in the target

genes (Figure S4). The most obvious difference between the

targets of known (conserved and non-conserved) and new

miRNAs is that the latter ones mostly belong to category III.

Indeed, out of the 44 new miRNA targets, only two were

category-I, three were category-II and 39 were category-III

targets (Figure 6; Table 4).

Next we asked whether there was a correlation between

the expression level of the new miRNAs and their ability to

target an mRNA for cleavage. We grouped the new miRNAs

based on the strength of the northern blot signal (Figure 5b).

We found cleavage products for one new miRNA (miRC12),

but not for five others (miRC1, miRC14, miRC15, miRC17 and

miRC20), with a relatively strong signal in leaf tissue. A

similar ratio (1:4) was found for the new miRNAs that

accumulate at a low level (with targets, miRC13; no targets,

miR4, miRC6, miRC18 and miRC21). Moreover, we also

found targets for new miRNAs (miRC2, miRC3, miRC5,

miRC9, miRC11 and miRC16), which do not accumulate to a

detectable level in the northern blot. Therefore, it seems that

there is no correlation between the expression level of new

miRNAs and whether we can find a target mRNA for them.

However, we must take into consideration that miRNAs are

often expressed in a very restricted way (Aung et al., 2006;

Valoczi et al., 2006; Kawashima et al., 2009; Voinnet, 2009);

therefore, the identified expression level may not perfectly

reflect the level of miRNAs in those cells where they are

expressed.

The new grapevine miRNAs target different genes with a

wide variety of predicted functions. Among the identified

targets of grapevine-specific miRNAs we found three protein

families, which were represented by more than two mem-

bers, such as proline-rich proteins, leucine-rich repeat

containing proteins and elongation factor 1. MiRC3 targets

four members of the proline-rich protein genes, which are

likely to be involved in defense responses (Fukuoka et al.,

2009). MiRC12 targets five transcripts encoding leucine-rich

repeat containing proteins, which are likely to be involved in

pathogen resistance (Table 4). The targeting of leucine-rich

repeat encoding genes by miRNAs was previously reported

from poplar (Lu et al., 2005) and Arabidopsis (Fahlgren et al.,

2007), but little is known about their contribution. MiRC9

targets elongation factor 1, a putative RNA-binding protein.

Interestingly, one of these proteins (eEF1A) was reported to

be involved in the replication and translation of various RNA

miRC1

U6

miRC2

U6

miRC3

U6

miRC4

U6

miRC5

U6

miRC6

U6

miRC7

U6

miRC13

U6

miRC8

U6

miRC9

U6

miRC10

U6

miRC11

U6

miRC12

U6

miRC14

U6

miRC18

U6

miRC19

U6

miRC16

U6

miRC21

U6

miRC15

U6

miRC17

U6

miRC20

U6

L T I B L T I B L T I BmiRNAs Leaves Tendrils Inflorescences BerriesmiRC1 43.9 2879.9 408.1 986.4miRC2 1.5 17.9 557.1 109.7miRC3 2.1 14.4 84.1 58.9miRC4 9.8 3.5 1.5 4.1miRC5 2.7 8.6 8.3 6.1miRC6 0.6 2.9 2.3 14.5miRC7 0.3 0.2 8.3 0.3miRC8_1 0.0 0.3 0.9 1.0miRC8_2 0.0 0.2 0.3 0.5miRC8_3 0.0 0.3 0.3 0.5miRC9 0.3 0.0 0.6 1.3miRC10 1.2 1.3 1.7 1.5miRC11_1 1.0 1.8 2.0 1.2miRC11_2 0.7 2.1 2.6 2.4miRC11_3 0.2 0.6 0.7 0.4miRC11_4 0.2 0.4 0.7 0.6miRC12 2.1 2.2 2.8 6.1miRC13 44.7 769.7 49.2 75.4miRC14 13.0 7.3 17.2 24.9miRC15 76.7 230.9 56.7 179.7miRC16 28.7 19.5 421.7 1705.6miRC17 580.7 680.8 1874.3 2180.8miRC18 77.3 52.6 51.0 46.0miRC19 0.6 1.6 3.8 2.0miRC20 143.7 72.8 106.4 241.2miRC21 115.8 206.4 69.0 134.8

Relative number of reads found in V. vinifera(a)(a) (b)

Figure 5. Expression of new microRNAs (miRNAs).

Normalized read numbers of new Vitis vinifera (grapevine)-specific miRNAs (only new miRNAs with sequenced miRNA*) found in different tissues are shown in

panel (a). Northern blot analysis of the new miRNAs is shown in panel (b). Low-molecular-weight RNA from different tissues was extracted, separated and

transferred to nylon membranes. Oligonucleotide probes were used to detect specific miRNAs, and a U6-specific probe was used to detect U6 RNA as a loading

control for each membrane. Key: L, leaves; T, tendrils; I, inflorescences; B, berries. (1) Expression profiles are expressed in reads (miRNA plus miRNA* plus variants

of the two derived from the hairpin) per million genome matching reads.

Grapevine microRNAs and their targets 11

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

viruses (Zeenko et al., 2002). Other targets that are worthy

to note are the receptor-like protein kinase gene targeted

by miRC23, the male sterility-like protein gene targeted by

miRC25 and a gene involved in salt tolerance, targeted

by miRC26.

DISCUSSION

Unusual sRNA content of grapevine

Several plant species, such as A. thaliana, O. sativa, S. lyco-

persicum and Medicago truncatula were shown to contain

substantially more 24- than 21-nt sRNAs (Rajagopalan et al.,

2006; Fahlgren et al., 2007; Morin et al., 2008; Moxon et al.,

2008a; Szittya et al., 2008). However, we observed an

unusually high level of 21-nt sRNAs compared with the 24-nt

class. Staining of total sRNA in gel confirmed the higher

abundance of 21-nt sRNAs in V. vinifera compared with

other plant species (Figure 1g). It is worthy to note that the

majority of the 21-nt reads matching to the grapevine gen-

ome are miRNAs (Table 1). However, as the number of

miRNA (families and their members) loci in the grapevine

genome is not higher than in other plant species (Tables S3

and S4), this cannot explain the higher level of 21-mer

miRNA expression. Importantly, we have sequenced sRNAs

from Pinot Noir clone ENTAV115, which is a widely culti-

vated clone. This is a highly heterozygous grapevine variety,

and its genome is suggested to be in paleopolyploid state

(Jaillon et al., 2007; Velasco et al., 2007), which may have an

important effect on miRNA processing. There are two other

reports that found the 21-nt class to be more prominent than

the 24-nt class, interestingly in two tree species: Pinus

cordata and Populus balsamifera (Barakat et al., 2007; Morin

et al., 2008). One possibility is that loci silenced by the 24-nt

heterochromatin siRNAs become transcriptionally silenced,

and therefore production of the 24-nt class declines over

years. Annual plants on the other hand must rapidly estab-

lish silencing through 24-nt heterochromatin siRNA at each

generation. Therefore, annual plants grown from seeds in

the laboratory may contain a high proportion of 24-nt class

sRNAs because the heterochromatin siRNA loci are trans-

criptionally more active than in plants that are several years

old, such as trees and grapevine.

Conserved miRNAs in grapevine

Most conserved miRNAs have been detected in grapevine

tissues, although their accumulation levels varied. Similarly

to other plant species, conserved miRNAs accumulated at a

higher level in inflorescences than in other tissues (Table 2;

Figure 3). Interestingly, in tendrils, which are a modified

inflorescence tissue adapted for climbing (Calonje et al.,

2004), most of the conserved miRNAs were expressed at a

very low or non-detectable level. One exception is miR395,

which was expressed at a higher level in tendrils than in

inflorescence tissue (Table 2; Figure 3). These findings

suggest that the miRNA-mediated regulation (or the lack of

this regulation) of gene expression has an important role in

the development of tendrils, which have a particular climb-

ing function.

0

1

2

3

4

5

6

7

8

9

miR

C11

miR

C12

miR

C13

miR

C16

miR

C23

miR

C25

miR

C26

miR

C2

miR

C3

miR

C5

miR

C9

New miRNAs

Num

ber

of t

arge

t si

tes

Cat IIICat IICat I

(a)

(b)

Figure 6. Summary of cleaved microRNA

(miRNA) target categories found with degra-

dome analyses. Details are given in Figures S3,

S4 and Tables S2 and S4 .

12 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

Almost all sequenced conserved miRNAs have the canon-

ical 21-nt-long DCL1 product, and very little variation has

been observed in grapevine tissues. This is a little surprising,

as Vazquez et al. (2008) have recently shown that precursors

representing most conserved miRNA families are also

independently processed by DCL3 (in addition to the

canonical DCL1 cleavage) to generate a new class of

bona fide miRNAs that are 23–25 nt in length, called long

miRNAs. The accumulation of long variant miRNAs in

A. thaliana was shown to be inversely correlated with the

level of miRNA conservation. They are likely to be depen-

dent on the organ-specific expression of DCL3 and the

hierarchical action of other DCLs. In the absence of DCL3,

certain miRNA precursors might originate 22-nt-long

miRNAs, presumably as a result of the action of DCL2. In

addition, miRNA start positions could vary between )2 and

Table 4 Targets of new grapevine microRNAs (miRNAs)

miRNA Target gene CategoryCleavagesite

Percentage ofcleavage at theexpected site

Reads atcleavagesite (tpb) Target gene annotation

miRC2 GSVIVT00005121001 3 782 0.25 64.42 Chlorophyllase 1miRC2 GSVIVT00015401001 3 891 1.75 257.69 ProteinmiRC2 GSVIVT00018198001 3 810 0.40 128.85 ProteinmiRC2 GSVIVT00020753001 3 1111 0.18 257.69 Peptidyl-prolyl cis-trans isomerasemiRC2 GSVIVT00021452001 3 145 1.69 386.54 Mitochondrial uncoupling proteinmiRC2 GSVIVT00023645001 3 1458 0.46 128.85 ProteinmiRC2 GSVIVT00023777001 3 782 0.18 64.42 Chlorophyllase 2miRC2 GSVIVT00038227001 3 157 2.73 257.69 ProteinmiRC3 GSVIVT00008224001 3 152 0.37 128.85 Metal ion bindinga

miRC3 GSVIVT00009989001 3 137 1.17 128.85 Proline-rich proteinmiRC3 GSVIVT00010025001 3 137 3.33 128.85 Proline-rich proteinmiRC3 GSVIVT00012879001 1 137 8.38 515.38 Proline-rich proteinb

miRC5 GSVIVT00000554001 2 1673 1.47 1288.46 chr 19 open reading frame 29miRC9 GSVIVT00018029001 3 1249 0.12 128.85 atp-dependent proteasemiRC9 GSVIVT00020598001 3 1693 0.08 128.85 ProteinmiRC9 GSVIVT00023150001 3 982 0.01 42.95 Elongation factor 1-miRC9 GSVIVT00024496001 3 1126 0.01 42.95 Elongation factor 1-miRC11 GSVIVT00002640001 3 1143 0.11 128.85 ProteinmiRC11 GSVIVT00025863001 3 150 1.33 128.85 ProteinmiRC12 GSVIVT00010574001 3 596 1.62 42.95 Leucine-rich repeat containingmiRC12 GSVIVT00010687001 3 596 1.45 42.95 Leucine-rich repeat containingmiRC12 GSVIVT00011082001 3 596 2.96 42.95 Leucine-rich repeat containingmiRC12 GSVIVT00012923001 3 596 2.07 42.95 Leucine-rich repeat containingmiRC12 GSVIVT00012926001 3 500 1.51 42.95 Leucine-rich repeat containingmiRC12 GSVIVT00018870001 3 399 1.32 515.38 4-hydroxyphenylpyruvate dioxygenasemiRC12 GSVIVT00029284001 3 587 3.75 128.85 disease resistance proteinmiRC12 GSVIVT00029984001 3 593 1.45 42.95 leucine-rich repeat containingmiRC13 GSVIVT00006484001 3 159 0.23 128.85 ProteinmiRC13 GSVIVT00020458001 3 190 2.94 128.85 Unnamed protein product [Vitis vinifera]miRC13 GSVIVT00031709001 3 94 0.33 128.85 ProteinmiRC13 GSVIVT00032526001 3 914 10.00 128.85 ProteinmiRC16 GSVIVT00002157001 3 791 0.35 257.69 Poly -bindingmiRC23 GSVIVT00028036001 3 1577 0.04 128.85 Sucrose synthasemiRC23 GSVIVT00038030001 3 2620 1.94 386.54 Receptor-like protein kinasemiRC25 GSVIVT00001890001 3 557 0.43 128.85 ProteinmiRC25 GSVIVT00003076001 2 936 0.70 1675.00 30s ribosomal protein s5miRC25 GSVIVT00022236001 1 828 1.41 515.38 Male sterility-likemiRC25 GSVIVT00023599001 3 783 0.04 128.85 flavine-containing monoxygenasemiRC25 GSVIVT00024587001 3 93 0.42 257.69 cinnamyl alcohol dehydrogenasemiRC25 GSVIVT00028964001 3 1296 1.44 128.85 Protein kinase family proteinmiRC25 GSVIVT00033658001 2 468 0.66 773.08 Vacuolar atpasesmiRC26 GSVIVT00021622001 3 758 0.39 128.85 Plastid division proteinmiRC26 GSVIVT00028126001 3 1823 0.81 128.85 ProteinmiRC26 GSVIVT00034774001 3 569 0.09 128.85 Salt tolerance expressed

aValidated in Carra et al. (2009).bPredicted by Carra et al. (2009).

Grapevine microRNAs and their targets 13

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

+2 nt away from annotated 5¢ ends, which might be caused

by the inaccuracy of DCL1 processing (Rajagopalan et al.,

2006). Our data suggest that long miRNAs are represented at

a much lower level in V. vinifera than in A. thaliana (Vazquez

et al., 2008), but at the moment it is not clear why. Perhaps

the high level of 21-nt-long sRNA species and the low level of

mis-processed miRNAs suggests a more active and accurate

DCL1 activity in grapevine tissues than in Arabidopsis.

Known non-conserved miRNAs

Plant MIR genes are proposed to arise from gene duplication

events to create perfect inverted repeat loci, which then

evolved by random mutations into short, imperfectly paired

hairpins (Allen et al., 2004; Axtell and Bowman, 2008). Those

miRNAs, which are not conserved, are believed to be evo-

lutionarily recent, and are generally represented by single-

copy MIR genes (Jones-Rhoades et al., 2006). Recently,

many non-conserved miRNAs were described in several

species (Rajagopalan et al., 2006; Barakat et al., 2007;

Fahlgren et al., 2007; Morin et al., 2008; Moxon et al., 2008a;

Szittya et al., 2008). Some of these non-conserved miRNAs

are not found in other species/families, but as sRNAs are

analysed in more species, several non-conserved miRNAs

are found in different phylogenetic families. We also found

26 non-conserved miRNAs in grapevine, although most of

them were present at a very low level. However, the low

number of sequence reads and weak northern blot hybrid-

ization signal do not rule out that they could be expressed at

a high level in specific cells. Indeed, it was demonstrated by

in situ hybridization analysis and promoter studies that

miRNAs accumulate spatially and temporally in a highly

restricted manner in N. benthamiana, A. thaliana and

M. truncatula (Aung et al., 2006; Valoczi et al., 2006;

Kawashima et al., 2009; Lelandais-Briere et al., 2009;

Voinnet, 2009). As expected, none of the three mono-

cot-specific miRNA families (miR437, miR444 and miR445;

Sunkar et al., 2005) were found. Few non-conserved miRNAs

(miR479, miR482, miR535, miR827 and miR894) were

expressed at a relatively high level, suggesting that they

may represent an intermediate status between the deeply

conserved and the less conserved miRNAs.

Grapevine-specific miRNAs

We have identified 21 grapevine-specific miRNAs with their

miRNA* star strands, which is an important pre-requisite for

new miRNA identification. New miRNAs were mapped to

the V. vinifera genome, and secondary structures were

predicted for each locus. Based on the hairpin prediction we

have identified an additional 21 miRNA candidates without

the miRNA* star strands. Unfortunately, we were not able to

test the DCL1 dependency of these new miRNA candidates

because grapevine DCL1 mutants are not available. Most of

the new miRNAs and candidates were mapped to a single

locus in the grapevine genome (Figure S2; Table 3). The

exceptions are miRC8 and miRC11, which could be pro-

duced from three and four loci, respectively. We have also

found candidate miRNAs with multiple loci such as miRC24,

miRC25, miRC28 and miRC30.

In plants, in contrast to animals, conserved MIR genes do

not usually form clusters; therefore, grapevine miRC13 and

miRC15 represent exceptions, as they are spaced only

224-bp apart on chromosome 17, with the same orientation

(Figure 4a and b). Although they are located very close to

each other, they show very different expression pattern in

inflorescences and berries. MiRC13 expression is low in

these tissues; however, miRC15 accumulates at a high level

(Figure 5b). This difference in the accumulation level could

be explained in two different ways. Despite of the close

proximity they are either expressed independently from

their own promoters, or their processing or accumulation

requires different tissue-specific factors.

New species-specific miRNAs are considered to be

young miRNAs that have evolved recently, and are often

expressed at a lower level than conserved miRNAs, as was

reported for Arabidopsis and wheat (Allen et al., 2004;

Rajagopalan et al., 2006; Fahlgren et al., 2007; Yao et al.,

2007). This observation is also true for many of the new

grapevine miRNAs identified here. However, few new

miRNAs were expressed at a high level in a tissue-specific

manner (Figure 5). In some cases we observed consider-

able inconsistency between the level of miRNAs identified

by Solexa sequencing and northern blot analysis; how-

ever, we do not know the explanation for these differ-

ences. It is possible that the probes used for northern blots

can detect miRNA species with a few mismatches that

were not considered by the bioinformatic analysis.

Another possibility is that during library generation or

sequencing some bias could occur for certain sequences

in some samples.

By searching miRBase (Griffiths-Jones et al., 2008) we

noticed that one of the new grapevine miRNAs (miRC9) is

very similar to a recently described miRNA in Aquilegia

coerulea (Puzey and Kramer, 2009). There are only two

mismatches between miRC9 and aqc-miR477e, and four

mismatches between miRC9 and other aqc-miR477 family

members (Figure S5). This raises the question whether

miRC9 should be classified as vvi-miR477. However, vvi-

miR477 already exists in miRBase (Jaillon et al., 2007), but

there are six mismatches between miRC9 and vvi-miR477,

and seven mismatches between miRC9 and ptc-miR477 (in

poplar); therefore, miRC9 should not be put into the miR477

family. The difference between miRC9 and vvi-miR477 is

highlighted by the fact that we did not identify any targets for

vvi-miR477 (Table S2), but found four targets for miRC9.

This demonstrates that these two miRNAs have different

functions in grapevine. However, miRNA sequences in

another species (A. coerulea) pull the two different

sequences into one family, suggesting that aqc-miR477 is

14 Vitantonio Pantaleo et al.

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

an evolutionary intermediate between vvi/ptc-miR477 and

miRC9. As miRNAs are sequenced in more and more

species, this will happen more often, leading to some

difficulties in miRNA classification.

Grapevine targets of known miRNAs

In grapevine, many conserved miRNA targets were predicted

(Jaillon et al., 2007; Velasco et al., 2007), although only a very

few miRNA targets were identified experimentally (Carra

et al., 2009). The recently developed high-throughput

experimental approach (Addo-Quaye et al., 2008; German

et al., 2008) allowed us to identify target genes for known and

new miRNAs identified in this work. As expected we identi-

fied a number of predicted targets for highly conserved and

known non-conserved miRNAs. Surprisingly, many highly

conserved miRNAs were identified in grapevine tissues

(Table 2), and did not have detectable sliced targets (e.g.

miR160, miR161 miR391, miR394 and miR395; Table S2). It is

possible that the levels of conserved miRNAs (e.g. miR160) or

sliced targets are below the detection level in leaf tissues, and

may be present in other tissues that have not yet been ana-

lyzed. Another explanation is that we used a computationally

predicted transcript set, which is likely to be incomplete.

Alternatively, these miRNAs inhibit target gene expression

through translational arrest, similar to miR156 and miR172,

which have been shown to regulate their target genes (SBPs

and AP2) predominantly by inhibiting their translation

(Aukerman and Sakai, 2003; Chen, 2003; Schwab et al., 2005;

Gandikota et al., 2007). Indeed, genetic and biochemical

evidence were recently provided that plant miRNA-guided

silencing has a widespread translational inhibitory compo-

nent (Brodersen et al., 2008; Lanet et al., 2009). Unexpectedly

in grapevine leaf tissue two target transcripts of miR172 (AP2-

domain-containing transcription factors) were sliced with a

very high efficiency (52 and 58%), although other targets of

miR172 were sliced with low efficiency (Table S2). Many of

the conserved miRNA targets were classified as category I

(Figure 6; Table 2) confirming the accuracy of our degra-

dome analysis, as it was previously shown that category I is

characteristic for conserved miRNA targets in Arabidopsis

(Addo-Quaye et al., 2008).

Targets of grapevine specific miRNAs

In grapevine leaf tissue we have identified eight targets for

grapevine-specific new miRNAs and three targets for miRNA

candidates (without sequenced star strands). One of the new

grapevine miRNA (miRC3) targets (GSVIVT00008224001,

metal ion binding protein) was previously identified and

another one (GSVIVT00012879001, proline-rich protein) was

predicted by Carra et al. (2009) (Table 4). The new grapevine

miRNAs target different genes with a wide variety of pre-

dicted functions. It may be worthy to note that miRC3 targets

three members of proline-rich protein genes, and that

miRC12 targets five transcripts encoding leucine-rich-

repeat-containing proteins, which are likely to be involved in

pathogen resistance (Table 4). The most obvious difference

between the targets of conserved and new miRNAs is that 39

out of the 44 new miRNA targets belong to category III

(Figure 6; Table S2), where the cleavage abundance was

lower than the median on the target transcripts (Addo-

Quaye et al., 2008). The finding that new miRNA targets

mainly fall into category III may also suggest that these new

miRNAs are young and not fully stabilized evolutionarily.

In this study we have confirmed the expression of

conserved, known non-conserved and new grapevine

miRNAs using high-throughput approaches to better under-

stand the role of miRNAs, which are tightly regulated at the

temporal and spatial levels (Valoczi et al., 2006; Voinnet,

2009). In addition, we have identified many targets of both

known and new miRNAs using recently developed tools for

the global identification of miRNA targets. Grapevine repre-

sents a model for cultivated woody plants, which usually

have highly heterozygous genomes and have been propa-

gated vegetatively for several hundreds of years. As these

characters are quite different for other model plants (e.g.

Arabidopsis), we expect to discover new roles of miRNAs in

post-transcriptional regulation. The unusually high level of

miRNAs is perhaps one of the important observations,

which could be a consequence of high heterozigosity,

although further studies are required to get a better insight

into the miRNA networks in grapevine.

EXPERIMENTAL PROCEDURES

Plant materials

Vitis vinifera of ‘Pinot Noir’ variety, clone ENTAV115 (Velasco et al.,2007), from a field collection was used as a source of plant tissue.Leaves (including stems) and tendrils were collected from the first tothe third internode from newly developing shoots. The inflores-cence tissues were collected upon their appearance. The smallberries were 1–4 mm in diameter.

Plants of A. thaliana col-0, S. lycopersicum MicroTom andN. benthamiana were grown in a growth chamber, with growthconditions of 24�C/18�C (day/night) and with 16 h of illumination perday.

Preparation of sRNA and degradome cDNA libraries for

Solexa sequencing

Vitis vinifera total RNA from different tissues was extracted byphenol/chloroform. Low-molecular-weight RNA (LMWR) was fur-ther enriched by using an RNA/DNA midi kit and following theinstruction manual (Qiagen, http://www.qiagen.com). Leaves,tendrils, inflorescences and berries sRNA fractions of 19–26 ntin length were isolated from LMWR by excision from 15% dena-turing polyacrylamide gels, and were ligated to Solexa adaptors(Illumina, http://www.illumina.com) without de-phosphorylatingand re-phosphorylating. The short RNAs were converted to DNA byRT-PCR following the Illumina protocol. The libraries from the fourtissues were sequenced by GENOME ANALYSER II (Illumina). Thedegradome cDNA library was prepared following the procedurespreviously described by German et al. (2008). Conversely to theshort RNA libraries, the degradome cDNA library was sequenced

Grapevine microRNAs and their targets 15

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x

with a custom-made sequencing primer (5¢-CCACCGAC-AGGTTCAGAGTTCTACAGT-3¢). Total sRNA from A. thaliana,S. lycopersicum and N. benthamiana was extracted using themiRVana kit (Ambion, http://www.ambion.com) from the aerial part(including stems and leaves).

RNA analysis

For the estimation of the ratio between the 21- and 24-nt sizeclasses, sRNAs from V. vinifera, A. thaliana, S. lycopersicum andN. benthamiana was carried out by loading 10 lg of LMWR fromeach plant species in a denaturing 15% polyacrylamide gel, fol-lowed by SYBR Gold staining (Invitrogen, http://www.invitrogen.com).

For northern blot analysis, 10 lg of LMWR from leaves, tendrils,inflorescences and berries was sepatared in a denaturing 15%polyacrylamide gel and blotted on Hybond-N+ membranes (Amer-sham, http://www.apbiotech.com). The probes of 21-mer DNAoligonucleotides (Table S5) that are reverse complementary tomicroRNA candidates were labeled with 32P-g-ATP by T4 polynu-cleotide kinase (NEB, http://www.neb.com).

Bioinformatics analysis

All Solexa data were processed by first converting FASTQ to FASTAformat, and then removing adaptor sequences with exact matchesto the first eight bases of the 3¢ adaptor. Any sequences withoutadaptor matches were excluded from further analyses. miRNApredictions were performed using MIRCAT (Moxon et al., 2008b) onthe V. vinifera assembly (Jaillon et al., 2007). Detection of con-served miRNAs was performed with MIRPROF (Moxon et al., 2008b),allowing two mismatches with mature miRNAs in miRBase(Griffiths-Jones et al., 2008).

The degradome analysis and the classification of target catego-ries were performed using the CLEAVELAND pipeline (Addo-Quayeet al., 2008, 2009) and predicted transcript set Vitis_vinif-era_mRNA_v1.fa from the Genoscope FTP site (http://www.cns.fr/externe/Download/Projets/Projet_ML/data).

ACKNOWLEDGEMENTS

We thank Gyorgy Bisztray and Tamas Deak for providingplant material. This work was supported by the European Unionfunded FP6 Integrated Project SIROCCO (LSHG-CT-2006-037900) toJB and TD.

SUPPORTING INFORMATION

Additional Supporting Information may be found in the onlineversion of this article:Figure S1. Normalized abundance of non-redundant 24-nt smallinterfering RNAs (siRNAs) from different tissues (leaves, tendrils,inflorescences and berries) in 0.2-Mb windows spanning the nuclearVitis genome.Figure S2. Predicted secondary structures of new and putativegrapevine-specific miRNAs.Figure S3. T-plots for targets of known microRNAs (miRNAs).Figure S4. T-plots for targets of grapevine-specific microRNAs(miRNAs).Figure S5. Alignment of miR477 family members and miRC9.Table S1. Longer versions of known microRNAs (miRNAs) ingrapevine.Table S2. Grapevine targets of known microRNAs (miRNAs).Table S3. Conserved microRNA (miRNA) genes in different plantspecies.Table S4. Expression of family members of known microRNAs(miRNAs) in grapevine.

Table S5. Oligonucleotides used for the detection of microRNAs(miRNAs).Please note: As a service to our authors and readers, this journalprovides supporting information supplied by the authors. Suchmaterials are peer-reviewed and may be re-organized for onlinedelivery, but are not copy-edited or typeset. Technical supportissues arising from supporting information (other than missingfiles) should be addressed to the authors.

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Grapevine microRNAs and their targets 17

ª 2010 The AuthorsJournal compilation ª 2010 Blackwell Publishing Ltd, The Plant Journal, (2010), doi: 10.1111/j.1365-313X.2010.04208.x