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MicroRNAs, the epigenetic memory and climatic
adaptation in Norway spruce
Igor A. Yakovlev1, Carl Gunnar Fossdal1 and Øystein Johnsen2
1
Norwegian Forest and Landscape Institute, PO Box 115, N–1431 Ås, Norway; 2University of Life Sciences, Department of Plant and Environmental
Sciences, PO Box 5003, N–1432 Ås, Norway
Summary
Author for correspondence:
Igor A. Yakovlev
Tel: +47 48 146583
Email: [email protected]
Received: 14 April 2010
Accepted: 7 May 2010
New Phytologist (2010)
doi: 10.1111/j.1469-8137.2010.03341.x
Key words: bud set, epigenetic, microRNA,
miRNA expression, reverse-transcription
polymerase chain reaction (RT-PCR).
• Norway spruce expresses a temperature-dependent epigenetic memory from
the time of embryo development, which thereafter influences the timing
bud phenology. MicroRNAs (miRNAs)are endogenous small RNAs, exerting epigenetic gene regulatory impacts. We have tested for their presence and differential
expression.
• We prepared concatemerized small RNA libraries from seedlings of two full-sib
families, originated from seeds developed in a cold and warm environment. One
family expressed distinct epigenetic effects while the other not. We used available
plant miRNA query sequences to search for conserved miRNAs and from the
sequencing we found novel ones; the miRNAs were monitored using relative real
time-PCR.
• Sequencing identified 24 novel and four conserved miRNAs. Further screening
of the conserved miRNAs confirmed the presence of 16 additional miRNAs. Most
of the miRNAs were targeted to unknown genes. The expression of seven conserved and nine novel miRNAs showed significant differences in transcript levels in
the full-sib family showing distinct epigenetic difference in bud set, but not in the
nonresponding full-sib family. Putative miRNA targets were studied.
• Norway spruce contains a set of conserved miRNAs as well as a large proportion
of novel nonconserved miRNAs. The differentially expression of specific miRNAs
indicate their putative participation in the epigenetic regulation.
Introduction
Norway spruce is an ecologically and economically important conifer having a wide geographic distribution and well
adapted to a large range of environmental conditions.
Conifers are masters of adaptation (Rohde & Junttila,
2008), despite exhibiting a very late sexual maturity and
long generation intervals (> 30 yr). Yet conifers have been
regarded as vulnerable to the rapid changes in temperature
by classical evolutionary means (Rehfeldt et al., 1999;
Rehfeldt et al., 2002). Thus, anticipated changes in global
climate have been considered to represent a significant challenge for sufficiently rapid adaptation, especially for traits
associated with the timing of the growth–dormancy cycles
in such trees vital for their growth and survival. However,
Norway spruce adjusts the adaptive performance by what
appears to be an epigenetic response mechanism that is
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calibrated by the temperature conditions prevailing during
embryo development. In both zygotic and somatic embryogenesis, the warmer the temperature conditions applied, the
later the regenerated plants from these embryos formed terminal buds in a common environment. Despite being
genetically identical the resulting adaptive change was large,
equating to a provenance separation of 4–6 degrees of latitude. Moreover, the propagated plants from somatic
embryogenesis displayed clonal variation in the memory
(Kvaalen & Johnsen, 2008) and there is family variation in
this trait (this work), strongly suggesting a genetic and heritable basis governing this epigenetic mechanism. Family
and clonal materials are therefore well suited for identification of the genes and other regulatory mechanisms involved
in this epigenetic memory mechanism.
The epigenetic memory could be understood as a type of
adaptive phenotypic plasticity, which lasts in the following
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generation and realized through specific epigenetic patterns
that established during development of the embryo and
affect DNA replication, recombination, repair and gene
expression. Previously, we have seen indications of correlation between the transcriptional regulation and the memory
expression (Johnsen et al., 2005b). Our first step toward
unravelling such a molecular mechanism is to identify the
genes and other regulatory elements involved in the epigenetic regulation of adaptive traits controlling the growth–
dormancy cycle in Norway spruce. Small RNAs are likely
candidate regulatory elements that could play a part in
this memory mechanism and thus were our target for
investigation.
Small RNAs have specific regulatory roles and been
implicated in epigenetic phenomena. They function in
several pathways for gene regulation or silencing. These
noncoding RNAs, which are 19–31 nucleotides (nt) long,
behave as sequence-specific triggers for mRNA degradation,
translation repression, heterochromatin formation and
transposon control. Small RNAs can be classified into
different groups based on their origin. In plants, small
RNA groups include micro-RNAs (miRNAs) and smallinterfering RNAs (siRNAs). miRNAs are noncoding RNAs
of an average length of 22 nt, and derived from hairpinstructured single-stranded precursors, that facilitate translation repression in plants (Bartel, 2004; Kim, 2005; Yang
et al., 2007; Axtell & Bowman, 2008; Morin et al., 2008;
Carthew & Sontheimer, 2009) or additionally engage
mRNA cleavage (Carthew & Sontheimer, 2009). siRNAs
are derived from double-stranded (ds) RNA precursors and
that silence genes by cleaving their target mRNAs (reviewed
in Rana, 2007). Regardless of type and size, small noncoding RNAs share one unifying function in cellular physiology: regulation of gene expression (Chu & Rana, 2007)
including epigenetic mechanisms.
Although significant progress has been made in identifying plant miRNAs and understanding their mechanism of
action, the discovery of novel miRNAs in plants on a genome-wide scale is still at the early stage. Most plant miRNA
studies have been done in angiosperms and few publications
involving miRNAs in conifers and other gymnosperms
exist. A total of 26 miRNAs from 11 families were identified in loblolly pine, possibly associated with the fusiform
rust gall disease (Lu et al., 2007); seven miRNA families
were loblolly pine-specific and four were conserved in other
species. Recently, five additional conserved miRNAs were
identified in loblolly pine seeds (Oh et al., 2008). In red
pine, 11 conserved miRNAs were found in needle tissues,
supporting the contention that many plant miRNA families
have been conserved during land plant evolution (Axtell &
Bartel, 2005). Sequencing of the Pinus contorta small RNA
transcriptome allowed identifying 18 highly conserved and
51 novel miRNA families (Morin et al., 2008). The
gymnosperm P. contorta have predominantly 21-nt long
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small RNAs and fail to produce significant amounts of the
24-nt small RNAs predominantly present in angiosperm
species. Gymnosperms have specific Dicer-like family
(DCL) genes not present in angiosperms (Dolgosheina
et al., 2008). There appear to be no publications dealing
with miRNA in spruce species until now.
We report here the identification of 44 miRNA in
Norway spruce for the first time. Using relative real-time
reverse-transcription polymerase chain reaction (RT-PCR)
we found 16 miRNAs with differential expression in transcript levels in the full-sib family expressing distinct differences in bud set, but not in the nonresponding full-sib
family, thus indicating their putative participation in the
epigenetic mechanism. Putative targets were found for 27
confirmed miRNAs. Most of target genes had unknown
functions but we found that four selected genes PaLPT4,
PaGaMYB, PaMYB10 and PaSPB13 are likely regulated by
miRNAs pab-miR100, 159a, 858 and 156c, and may also
be involved in or at least correlated with the epigenetic
memory regulation.
Materials and Methods
Plant material, growth conditions and sample
collection
We used progenies from the two extreme full-sib families of
Norway spruce (Picea abies (L.) Karst) in regard to the
epigenetic memory mechanism with known differences in
timing of bud set. We used progenies from two full-sib
families of Norway spruce with known differences in the
timing of bud set, as assessed by growing the seedlings in a
glasshouse experiment in the autumn of 2005 (Johnsen
et al., 2005a). Within each family seeds from plants regenerated after embryogenesis in cold environment (CE) and
seeds after embryogenesis in a warm environment (WE)
were used, giving a total of four seed types. The seeds were
sown at 22C under continuous light (long day = LD) in
eight chambers. After 8 wk growth, four of the chambers
were programmed to give short days (12 h light + 12 h
darkness; SD). Progeny of family 1 showed the lowest
difference in bud set between CE and WE and were considered as ‘epigenetically indifferent’. Progeny of family 6
showed the greatest difference in bud set between CE and
WE, was considered ‘epigenetically responsive’. Ten shoots
were harvested from both SD and LD treatments for 6 d
and 20 d from the onset of SD treatment and immediately
frozen in liquid nitrogen. Collections were done 4–5 h after
onset of light in the morning.
Small RNA isolation and library construction
Small RNAs were isolated from 80 mg of tissue using the mirPremier microRNA Isolation Kit (SNC-50; Sigma-Aldrich,
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St. Louis, MO, USA), according to the manufacture’s
instruction. The quality of small RNA was assessed by
Agilent 2100 Bioanalyzer with RNA 6000 Nano Kit
(Agilent, #5067-1511, Santa Clara, CA, USA). Small RNA
preparations were stored at )80C.
To identify small RNAs, we used a direct cloning and
sequencing approach, allowing for high-efficiency identification of new miRNAs (Zhang et al., 2006a). We made
two small RNA libraries using IDT’s miRCat Small RNA
Cloning Kit (Integrated DNA Technologies, Coralville, IA,
USA) by following the manufacturer’s instructions. For
library construction we used small RNA extracts (nearly
1 lg) from family 6, which had the highest ‘memory’
response. The first library contained concatenated small
RNAs expressed in progeny after embryogenesis in WE in
response to 20 d of SD treatment (WEL) and the second
contained concatenated small RNAs expressed in progeny
after embryogenesis in CE in response to 20 d of SD treatment (CEL). After concatamerization, small RNAs were
cloned into pDrive vector using PCR Cloning Kit
(Qiagen).
Small RNA sequencing and discovery of novel
miRNAs
The small RNA libraries were partly sequenced at the ABIlab of the Departments of Biology and Molecular
Biosciences (University of Oslo, Norway). Trace files were
processed for removal of vector sequences and poor-quality
regions as well as contigs assembly with the help of secman
ii sequence analysis software (DNAStar Inc., Madison, WI,
USA). The sequences obtained were manually scrutinized
for removal of linker ⁄ connectors in concatamer units. The
small RNA sequences were assumed to be the sequence
between the 5¢ and 3¢ linker ⁄ connectors, and small RNAs
obtained were grouped based on their sequences. The small
RNAs identified were compared with all published mature
miRNAs sequences from the miRBase Sequence Database,
release 14.0 (http://www.mirbase.org/index.shtml) (GriffithsJones et al., 2008). Comparison was done using blastn
procedure with word size 7. Similarities with a score > 32
or an E-value of )2 were considered a hit (allowing a maximum of 2 nt mismatches).
All the small RNAs identified were also searched against
the National Centre of Biotechnology Information (NCBI)
expressed sequences tag (EST) database restrained by Picea
taxa. We allowed only up to one mismatch between the
small RNA and matching site at the forward strain orientation (sense hit). Hairpin structures were predicted using
mfold software (Zuker, 2003) (http://frontend.bioinfo.rpi.
edu/applications/mfold/cgi-bin/rna-form1.cgi) and RNAfold
web server (Gruber et al., 2008) (http://rna.tbi.univie.ac.at/
cgi-bin/RNAfold.cgi). It is known that plant pre-miRNAs
vary from approx. 80 to approx. 200 nt in length (Zhang
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et al., 2006b), so we select regions of different length, from
100 to 400 nt on either side of the small RNA sequence for
folding analysis.
RNA sequences were thought of as miRNA candidates
only if they fitted the following criteria: a RNA sequence
could fold into an appropriate stem–loop hairpin secondary
structure; a mature miRNA sequence site in one arm of the
hairpin structure; miRNAs had < 6 mismatches with the
opposite miRNA* sequence in the other arm; predicted secondary structures had higher folding free energy indexes
(MFEIs), negative minimal folding free energies (MFE <–
25 kcal mol)1) and 30–70% A + U contents (Zhang et al.,
2006b). These criteria significantly reduced assignment of
false positives (Ambros et al., 2003).
Discovery and analysis of conserved micro RNAs
To identify potential Norway spruce conserved miRNAs,
we defined a total of 274 previously known wooden tree
species miRNAs (37 from Pinus taeda and 234 from
Populus trichocarpa) from the miRNA Registry Database
(Release 14.0, September 2009: http://www.mirbase.org/)
as reference set of miRNA sequences. In addition, 715
known miRNA sequences from Arabidopsis thaliana, Oryza
sativa, and Zea mays were chosen. To avoid the redundant
or overlapping miRNAs, the repeated sequences of
miRNAs within the above species were removed and the
remaining sequences were used as query sequences. As only
mature miRNAs, rather than miRNA precursor sequences,
were conserved in plants (Zhang et al., 2006b), mature
miRNA sequences were the focus of blast search. We used
blast search against the spruce ESTs and nr databases,
which were obtained from the NCBI Genbank nucleotide
databases (http://ncbi.nlm.nih.gov). Any sequences not
encoding protein located in forward strain with 0–1
mismatch to analysed mature miRNA were considered as
candidate miRNA genes and used for folding analysis.
Candidate mRNAs were checked using the web-based
computational software mfold as described earlier.
Prediction of miRNA targets
When looking for potential mRNA targets of miRNAs, we
used a blastn pattern search of obtained small RNA
sequences against NCBI EST and nucleotide databases,
confined to Picea taxa. We allowed only up to four mismatches between the candidate miRNA and miRNA target
site at the reverse and compliment strain (antisense hit) in
this prediction. The extracted sequences (ESTs) were
combined into contigs to get full-length sequences when
possible. We used a tblastx search of the ESTs nucleotide
sequence against the NCBI database to identify putative
gene homologues. Similarities with an E-value less than e)10
were considered a hit.
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Relative real-time RT-PCR
Transcript abundance of the selected small RNAs were
determined for the families 1 and 6 with relative real-time
RT-PCR. cDNAs were synthesized from 600 ng of small
RNA with the NCode miRNA First-Strand cDNA
Synthesis Kit (MIRC-50; Invitrogen) following the manufacturer recommendations. Real-time RT-PCR amplification was performed using NCode SYBR GreenER miRNA
qRT-PCR Kit (MIRQER-100; Invitrogen) in a 25 ll reaction volume, using 2 ll of a diluted cDNA solution already
described as template and 200 nM of each primer.
Reactions were conducted on the 7500 Fast Real-time PCR
System (Applied Biosystems, Foster City, CA, USA) using
the Invitrogen recommended cycling conditions. After
PCR, dissociation curves were carried out to verify the
specificity of the amplification. There were three biological
replicates for each sample. All expression levels were normalized to geometric mean of three selected ribosomal and
transfer RNA genes (Pa4.5S, Pa5S and PatRNA-R), showing most similar expression profiles among eight genes
tested (see the Supporting Information, Table S1, Fig. S1).
Forward primers were designed based on mature miRNA
sequence. If Tm of mature miRNA was < 60C, it had been
adjusted by adding Gs and Cs to the 5¢-end and ⁄ or As to
the 3¢-end of the miRNA sequence. The list of miRNAs
studied and their primer sequences are shown in Table S2.
To verify the specificity of the miRNA amplification, we
analysed several PCR samples for each miRNAs on 2% agarose gels with ethidium bromide (EtBr) visualization of
bands. Reverse primer was supplied with the NCode
miRNA First-Strand cDNA Synthesis Kit (MIRC-50;
Invitrogen).
Transcript abundances for the selected miRNAs target
genes ESTs were determined in the full-sib family 6. The
list of the ESTs and their primer sequences can be found
in Table S3. Primers were designed using primer3 online
software (Rozen & Skaletsky, 2000) available at http://
frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi with
calculated Tm of 70C and amplification product not
> 120 bp. cDNA was synthesized from 300 ng of total
RNA with the TaqMan Reverse Transcription kit (Applied
Biosystems) in 50 ll reaction volume and diluted three
times. Real-time RT-PCR amplifications were conducted
on the 7500 Fast Real-time PCR System (Applied Biosystems) using the default cycling conditions. After each
reaction, which included a no-template control, dissociation curve analyses were carried out to verify the specificity
of the amplification. There were three biological replicates
and all expression levels were normalized to actin.
Data acquisition and analysis were done using 7500system SDS software for absolute quantification and
MS Excel software as described previously (Johnsen et al.,
2005a).
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Results
Small RNA sequencing and analyses
Two small RNA libraries were constructed from young
seedlings of Norway spruce family 6 showing greatest differences in epigenetic response to the temperature conditions
during embryogenesis. The first library contained small
RNAs expressed in response to 20 d of SD treatment in the
progeny after embryogenesis in WE (WEL) and the second
contained small RNAs expressed in progeny after embryogenesis in CE (CEL). A total of 328 individual concatemerized clones were isolated and sequenced in both directions,
yielding 323 small RNA sequences ranging in size from 17
to 24 nucleotides (Table 1 & Table S4). Sequence analyses
revealed 191 distinct small RNAs; 103 different small
RNAs were found only in WEL and 75 in CEL. Just 13 of
the distinct small RNAs were shared between the two
libraries. Most frequent small RNAs appear to be pabsmR02a (28 entries) and pab-smR02b (14 entries). Length
distribution of small RNAs is summarized in Fig. 1. Both
libraries contain predominantly small RNAs with 21 nt
length, followed by small RNAs with 22 nt. Other length
variants are represented by a few sequences.
We checked all of the small RNAs for similarity to the
miRNAs described earlier, placed into miRBase Database
(release 14.0). Only four small RNAs had sequences identical, or highly similar, to those of conserved plant miRNAs
that belongs to miR159, miR529, miR949 and miR951
families. All the other 195 novel small RNAs had no
matches in the miRNA database.
Discovery of novel P. abies miRNAs using spruce ESTs
We further searched with the small RNA sequence patterns
obtained against the NCBI est_others ESTs and nucleotide
collection databases confined to Picea (taxid:3328), allowing
up to four mismatches between the small RNA and
Fig. 1 Length distribution of unique small RNA sequences from
Picea abies (light bar, 193 sequences from WEL; dark bar, 130
sequences from CEL)
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matching site. We found hits for 98 of the small RNAs
among spruce ESTs, while 101 small RNAs showed no
matches with known transcripts (Table S4). These 99 small
RNAs with no matches (excluding two small, RNAs which
were identified among conserved miRNAs) were not further
analysed owing to lack of any information about their
origin sequences or putative targets. For the conserved
pab-miR949 ⁄ pta-miR949 and pab-miR529 ⁄ osa-miR529b
we found no matching sequences among the Picea sequences
publicly available, so designation of these as miRNAs is
based solely on their sequence matching known miRNAs.
Among the contigs with matches to small RNAs, we
selected candidate miRNA genes among sequences not
coding for a protein and containing a mature small RNA
sequence located in forward strand orientation (sense hit),
allowing up to one mismatch. In total, we found 37 such
candidate miRNA genes. Sequences upstream and downstream of the matching region ( 200 bp) for the 37
candidate miRNAs were used to predict the secondary
structure using mfold and RNAfold web servers. Stable
stem–loop miRNA precursor structures were identified for
25 of the candidates. The EST ES261905 was predicted to
be a precursor for both pab-miR002a and pab-miR002m
situated on different shoulders of stem–loop structure.
Contig FD735299 was predicted to be a precursor for two
copies of novel pab-miR154ns located opposite each other
on 5¢ and 3¢ arms of the precursor. All the other ESTs were
predicted precursors for single miRNAs. These small RNAs
were designated as pab-miRNAs (Tables 1, S5, Fig. S2).
For conserved pab-miR159a ⁄ pta-miR159a we identified
several ESTs with matching region, but stem–loop hairpin
structure was not confirmed, therefore we define
pab-miR159a, pab-miR949 and pab-miR529 as miRNAs,
based solely on their sequence matching to previously
described miRNAs despite the lack of in silico precursor
structure confirmation.
The designated 28 miRNAs could not be combined into
miRNA clusters and miRNA families. Each miRNA is
likely a single representative of their miRNA families. Only
pab-miR144a and b showed similarity to each other (but
still 7 bp differences) and we considered them tentatively as
representatives of the same novel miRNA family. Four
miRNAs – pab-miR159a, miR949, miR951 and miR529b
– are likely single representatives of four miRNA families
conserved in other plant species (loblolly pine, Arabidopsis
and rice). All other putative families obtained were novel
(Table 1).
Discovery and analysis of conserved microRNAs in
Norway spruce
We searched the defined reference set of plant miRNAs by
blastn against known spruce ESTs set at the NCBI EST
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database. The ESTs having high similarities (allowing with
0–1 mismatches) to the reference miRNA on the forward
strand (sense hit) were selected as candidate miRNA genes,
while transcripts (ESTs) containing up to four mismatches to
miRNA sequence on reverse strand were designated as
putative miRNA targets. In total, by screening of nearly 1000
described miRNAs from other plant species, we identified 60
spruce EST contigs containing miRNA matching regions.
We selected 32 of these ESTs in which miRNA-matching
region was located in the forward strand, as microRNA gene
candidates. A careful evaluation of the predicted secondary
structures, using the criteria described in the method section,
allowed us to confirm stem–loop hairpin-folding patterns for
16 of these candidates (Table 1). These predicted precursor
sequences and microRNA homologues were further considered as Norway spruce microRNAs. For the remaining 15
contigs, no indications of hairpin structures were found.
The sixteen such identified Norway spruce miRNAs were
found to fall into 11 miRNA families: miR396 and miR483
each has three members, miR160 and miRNA165 ⁄ 166 has
two members, while for other miRNA families, such as
miR395, miR397, miR535, miR947, miR951, miR1311
and miR1836, only one member was predicted. Most of
these microRNAs (14 of 17) were similar to known loblolly
pine and Populus miRNAs and only few matched other
plant species miRNAs.
Prediction of the potential miRNAs and small RNAs
targets in Norway spruce
To find the putative target genes regulated by the novel and
conserved miRNAs, we made pattern blast search against
NCBI EST and nucleotide databases, confined to Picea
taxa. We allowed only up to four mismatches between the
candidate miRNA and miRNA target site at the reverse and
compliment strain (antisense hit) in this prediction. The
mature sequences of the 44 confirmed pab-miRNAs (Table 1)
and 45 unconfirmed conserved miRNAs (Table S6) were
analysed.
Putative functions of the potential targets were assigned
based on similarity to putative annotated homologues by
obtained contigs blastx against NCBI protein database.
Among the confirmed pab-miRNAs, five of the putatively
targeted ESTs were homologous to TIR(CC) ⁄ NBS ⁄ LRR
disease-resistance proteins from pine species. The predicted
targeted ESTs for 11 of the pab-miRNAs showed no
significant similarity to known genes and four of the
pab-miRNAs corresponded to hypothetical or unnamed
protein products. For 18 of the pab-miRNAs we did not
find any putative targets. Thus, 29 pab-miRNAs may target
Norway spruce genes that are not yet sequenced (Table 1).
Only six pab-miRNAs putatively targeted to annotated
functional genes and transcription factors.
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pab-miR029
pab-miR031
pab-miR057
pab-miR061
pab-miR065
pab-miR070
pab-miR078
pab-miR080
3
4
5
6
7
8
9
10
GACGCCCAAAACUGAAGGUCA
GACAGAAGAUAGACUUUGGUC
CUUGCAACUCUGCCUUGGCUUA
AUUAAGGGUGCGGGUGCGGCU
UUGUCGCCUGGUCGUUGUGGG
CGAGCUACCAUCGUGACGAUC
UAGCCCCUGACUUCAACAUGAG
AGAGGGUGCUCAUGAACUGCUC
UCUGGGCCCCGGUGGUUUAUGA
pab-miR02m
2
Sequence
UCACAUCUGGGCCACGAUGGUU
Name
Novel miRNAs1
1
pab-miR02a
Family
21
21
22
21
22
21
22
22
22
22
Length,
nt
3¢
3¢
5¢
3¢
5¢
5¢
5¢
5¢
5¢
5¢
Arm
EX369017
DR469293
EX404488
EX379118
FD739801
EX427832
EX427311
EX326419
ES261905
ES261905
miRNA
containing EST
EX412904;
CO484875
(3 mismatches)
DR451014
(3 mismatches)
EX385049
(4 mismatches)
–
–
–
EX417859
(3 mismatches)
DR524266
(3 mismatches)
DR543641
DR475593
Target
No significant
similarity found
BAC83199.1 – TIR ⁄
P-loop ⁄ LRR
disease resistance
protein-like protein
(Oryza sativa
Japonica Group)
AAY78890.1 –
CC-NBS-LRR
resistance-like
protein (Pinus
lambertiana)
–
–
–
AAM28917.1 –
putative
TIR ⁄ NBS ⁄ LRR
disease resistance
protein (Pinus
taeda)
No significant
similarity found
Q03682 –
BIP2_TOBAC
Luminal-binding
protein 2 (BiP 2)
(78 kDa glucoseregulated protein
homolog 2-Hsp70
family)
NP_172027.1 – thiF
family protein
(Arabidopsis
thaliana) molyb
dopterin
biosynthesis protein
MoeB
Target gene function
335
(860) ⁄ 2e-90
366
(939) ⁄ 2e-99
–
–
–
–
147
(372) ⁄ 2e-42
311
(796) ⁄ 5e-83
59
(142) ⁄ 9e-08
–
Score ⁄ E-value
Table 1 Isolation and identification of conserved and novel Norway spruce specific microRNAs (miRNAs) and their putative targets (miRNA precursors are shown in the Supporting
Information Table S5 and Fig. S2)
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pab-miR100
pab-miR105
pab-miR113
pab-miR119
pab-miR122
pab-miR131
pab-miR132
pab-miR144a
pab-miR144b
12
13
14
15
16
17
18
19
20
pab-miR154
pab-miR157
pab-miR158
pab-miR173
pab-miR086
11
21
22
23
24
Name
Family
Table 1 (Continued)
UGGGAACCUGACGGGCCUCCA
UGGCGCUAGAAGGAGGGCCU
UGUGAUCAAGAUCAGACUACCA
GGCUUGCGAGGAUAGGAAAAA
UUUAAAUGCCUUAAAUUCCCGA
UCAGAUGCUUUAAAUUCCCGA
UUUCGGAGAAAUGGAUAAGAC
AUGAUCUGCCAUUAUCCUUGA
UCACACAACAUUGCUCGUACA
UUUUUCCAACUCCACCUAGACC
GUAAGUGGUUAUGAUCUGGAC
UAGACUCUAUCAGCCUUGUCC
AAUCUCUUGGUGCUUAUUCGC
UAAACAGUGCCCACCCUUCAUC
Sequence
21
20
22
21
22
21
21
21
21
22
21
21
21
22
Length,
nt
5¢ ⁄ 3¢
5¢
5¢
5¢
5¢
5¢
5¢
3¢
5¢
5¢
5¢
5¢
5¢
3¢
Arm
FD735299
EX383067
DV995132
ES258251
DR551675
DR584076
EX359902
CO213440
(1 mismatch)
DR567751;
CO212009
EX443975
DR499063
EX312498
DR571316
CO225835
miRNA
containing EST
–
–
–
–
EX343057; (2 mismatches)
EX370466 (3 mismatches)
–
–
–
–
DR491334 (1 mismatch)
EX406540 (2 mismatches)
EX408626
DR474361 (1 mismatch);
EX370463 (2 mismatches)
EX358490 (4 mismatches)
EX315011 (3 mismatches)
Target
CAN67425.1 –
hypothetical
protein (Vitis
vinifera)
CAO63167.1
– unnamed protein
product (Vitis
vinifera)
–
–
–
–
NP_568201.1 –
positive
transcription
elongation
factor – Spt4 ⁄
zinc ion binding
(Arabidopsis
thaliana) EAY72686.1 –
hypothetical
protein OsI_000533
(Oryza
sativa (indica
cultivar-group))
No significant
similarity found
–
AAM28917.1 –
putative TIR ⁄ NBS ⁄ LRR
disease resistance
protein (Pinus
taeda)
–
–
–
No significant
similarity found
Target gene function
–
–
–
–
119
(299) ⁄ 2e-42
114
(285) ⁄ 1e-23
–
–
–
–
212
(539) ⁄ 3e-53
–
185
(470) ⁄ 4e-45
194(494) ⁄ 6e-48
–
Score ⁄ E-value
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Name
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39
38
37
36
35
34
33
32
31
30
29
28
27
26
pab-miR535 ⁄
osa-miR535
pab-miR482a ⁄
pta-miR482a
pab-miR482e ⁄
pta-miR482a
pab-miR482f ⁄
pta-miR482a
2
pab-miR529b ⁄
osa-mir529b
pab-miR166a ⁄
pta-miR166a
pab-miR395 ⁄
ptc-miR395a
pab-miR396a ⁄
pta-miR396
pab-miR396b.1 ⁄
ptc-miR396a
pab-miR396b.2 ⁄
ptc-miR396a
pab-miR397 ⁄
ptc-miR397a
pab-miR160.1 ⁄
ptc-miR160a
pab-miR160.2 ⁄
ptc-miR160a
pab-miR165a ⁄
ath-miR165a ⁄
pta-miR166a
Conserved miRNAs
2
pab-miR159a ⁄
25
pta-miR159a
Family
Table 1 (Continued)
UGACAACGAGAGAGAGCACGC
AGAAGAGAGAGAGUACAGCCU
UCUUUCCUACUCCUCCCAUUCC
UCUUCCCUAUUCCUCCCAUUCC
UCUUCCCUACUCCUCCCAUUCC
UCAUUGAGUGCAGCGUUGACG
UUCCACGGCUUUCUUGAACUU
UUCCACAGCUUUCUUGAACUG
UUCCACAGCUUUCUUGAACUA
CUGAAGUGUUUGGAGGAACUU
UCGGACCAGGCUUCAUUCCUU
UCGGACCAGGCUUCAUUCCUC
UGCCUGGCUCCCUGUAUGCCA
UGCCUGGCUCCCUGUAUGCCA
UUGGAUUGAAGGGAGCUCCA
Sequence
21
21
22
22
22
21
21
21
21
21
21
21
21
21
20
Length,
nt
n
No
hairpin
structure
Arm
ES663083
n
GH281854
EF087815
EX443975
CO480982
(1 mismatch)
DR451001
EX431337
EX431337
EX396486
GE475070
GH284233
DR468340
CO484471
EX379646;
CO226626
miRNA
containing EST
–
EX357165
(2 mismatches)
–
–
EX356746;
DV996417;
BT070419;
EF677723
–
–
CO481346
CO481346
–
ES874991
DR519274
(3 mismatches)
EX444394; EX442742
(2 mismatches)
EX411402
(1 mismatch)
Target
CAN69561.1 –
hypothetical
protein
(Vitis vinifera)
–
–
–
–
AAK37828,
AF132124 laccase
(Pinus taeda)
No significant simi
larity found
No significant simi
larity found
–
BAB85242.1 – tran
scription factor
GAMyb (Oryza
sativa Japonica
Group)
ACI13681.1 putative
auxin response
factor ARF16
(Malus · domestica)
ABD75310.1 class III
homeodomainleucine zipper
protein C3HDZ2
(Pseudotsuga
menziesii)
No significant simi
larity found
–
Target gene function
–
51 (121) ⁄ 9e-05
–
–
–
475 (1223) ⁄ 2e-132
–
–
–
–
–
535 (1378) 2e-150
192 (487) 3e-47
83 (205) ⁄ 2e-14
Score ⁄ E-value
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Journal compilation New Phytologist Trust (2010)
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73
(178) ⁄ 8e-12
Expression of selected Norway spruce miRNAs for
epigenetically different samples
AGCUCUGAUACCAUGUUAGAUU
44
n, No exact full-length matching in the NCBI spruces expressed sequence tags (ESTs) Database.
1
Numbering just for internal reference and not corresponds to the miRNA family numbers at the miRBase.
2
Obtained from sequenced libraries.
22
22
UCAGAGUUUUGCCAGUUCCGCC
pab-miR1311 ⁄
pta-miR1311
pab-miR1863a ⁄
osa-miR1863
43
UGUUCUUGACGUCUGGACCACG
42
The Authors (2010)
Journal compilation New Phytologist Trust (2010)
Among the predicted (but unconfirmed) conserved
spruce miRNAs, 22 of the putative target genes were
homologous to structural genes, as well as transcription
factors. For 10 conserved miRNAs, no target was found,
and 8 more matched genes with unknown function.
EX357058
EX352990
–
DR565328 EX311606
ES248264
157
(396) ⁄ 6e-37
DR563813
DR473257
5¢
22
22
41
UCUCCGGGAAUCCAAUGCGCCU
UAUCGGAAUCUGUUACUGUUUC
pab-miR947a ⁄
pta-miR947
2
pab-miR949 ⁄
pta-miR949
2
pab-miR951a ⁄
pta-miR951
40
22
n
n
DR547733
(2 mismatches)
EX417324
–
–
No significant
similarity found
No significant
similarity found
AAM28917.1 –
putative TIR ⁄ NBS ⁄ LRR
disease resistance
protein (Pinus
taeda)
No significant
similarity found
ABK21509 unknown
(Picea sitchensis)
EX312403
EX312737
Score ⁄ E-value
Sequence
Name
Family
Table 1 (Continued)
Length,
nt
Arm
miRNA
containing EST
Target
Target gene function
Research
With real-time RT-PCR we characterized the expression of
all defined pab-miRNAs in the Norway spruce seedling
from the Norway spruce full-sib family 1 (F1, having low
‘epigenetic memory’ response) and family 6 (F6, having a
distinct ‘epigenetic memory’) after embryogenesis in CE
and WE at LD conditions and after SD treatment. The
expression of seven conserved and nine novel miRNAs
showed significant differences in transcript levels in the fullsib family expressing distinct differences in bud set, but not
in the nonresponding full-sib family.
Among novel miRNAs only pab-miR144a showed large
differences in transcript abundances between WE and CE
from F6 samples at SD6 and small differences for F1
(Fig. 2). The largest group of miRNAs – pab-miR080, 100,
105, 119, 122, 132, 144a,b and 157 – showed large differences in amounts of transcript in the SD20 samples for F6
and showed small differences between WE and CE for the
SD20 samples of F1. Thus, these miRNAs showed transcription patterns compatible with being putatively involved
in, or affected by the epigenetic memory mechanism.
Among these, the most interesting were pab-miR105, 119,
122, 132 (greatest difference between WE and CE SD20
samples at F6) and miR144a (significant difference between
WE and CE samples for both SD6 and SD20 at F6); These
were considered as being the more likely candidate
regulators, which could possibly involved in the molecular
epigenetic memory mechanism.
Among the conserved pab-miRNAs we found several
miRNAs (pab-miR395, 396a, 396b, 535, 947 and 951)
that showed significant difference in expression between
WE and CE samples for F6 family and virtually no difference for F1 family progeny (Fig. 2). In addition, pabmiR160 and 395 had difference in transcript levels between
WE and CE samples of family F6 for both day 6 and day
20, but were found to have significant differences for F1
under SD20 conditions and no differences under LD for all
F1 samples. These pab-miRNAs could potentially be
involved in epigenetic memory regulation. The other pabmiRNAs studied did not reveal any consistent patterns of
expression and are probably not related to the epigenetic
phenomenon.
The conserved pab-miRNAs found tended to have higher
expression (Ct –9 to 23) than the novel miRNAs (Ct –20
to 33). The distinct peak after melting curve analysis and
consistent expression patterns of pab-miRNAs observed
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Fig. 2 Transcript profiles of selected Norway
spruce novel(n) and conserved microRNAs
(miRNAs) putatively involved in epigenetic
regulation. Samples are seedlings from
families 1 and 6 with low and high epigenetic
memory response (correspondently) after
cold (CE) and warm (WE) environment
treatment at days 6 and 20 under short day
(SD) and long day (LD) photoperiod
conditions. Transcript level was measured as
the difference between geometric average of
three reference genes – Pa4.5S, Pa5S and
Pa-tRNA_R (endogenous control) and the
chosen transcripts relative to the mean value
for the genes targets ()dCt). Bars indicate
standard error of means. Numbering of novel
miRNAs just for internal reference and not
corresponds to the miRNA family numbers at
the miRBase.
strongly support that they were correctly defined as
miRNAs.
Study of pab-miRNAs and their putative target
coexpression and verification of regulation
To test and support regulation of putative target genes by
miRNAs, we tried to confirm antagonistic expression of the
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miRNA to its predicted target mRNA (i.e. establish if there
was a relationship between small RNA transcript abundance
and transcript-level changes of their putative target gene
mRNA). For this purpose, we selected conserved and novel
miRNAs (even if we did not confirm stem–loop precursor
structures in some cases) for which known functional gene
targets were predicted. We studied this, using relative RTPCR transcript-level differences of miRNAs and target gene
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mRNAs in parallel for the same samples from the seedlings
of Norway spruce family 6 (epigenetically responsive), from
CE and WE embryogenesis at LD and after 6 d and 20 d
of SD. In total, we tested 10 conserved and 2 novel
miRNAs (Table S7).
Finally, we picked four miRNA-mRNA pairs that were
significantly different in transcript abundances of both
miRNAs and mRNAs using the same samples (Fig. 3). We
expected that the abundance of target mRNA became
reduced when the presence of small RNAs transcripts
increased and vice versa.
PaGaMyb (gibberellic acid MYB transcription factor)
seemed to be regulated by pab-miR159a (pta-miR159a), as
shown in Fig. 3. Significantly decreased amounts of
miR159a transcripts at day 6 to day 20 coincided with the
accumulation of targeted mRNAs for WE samples, both
under SD and LD. For the CE samples, there was no significant difference in transcript abundances of miRNAs and
mRNAs. A similar pattern was found for transcription
elongation factor PaSPT4 mRNA, putatively regulated by
pab-miR100 (Fig. 3). For pab-miR858 targeted PaMyb10
(transcription factor MYB10) the results were less clear
(Fig. 3). A significant decrement of pab-miR858 transcripts
from day 6 to day 20 under SD for CE samples was accompanied by a higher abundance of putative targeted mRNAs.
However, no interrelation in levels was found for WE
samples. At LD conditions, the increment of siRNAs did
not lead to a decrease of mRNAs. PaSPB13 (Squamosa promoter-binding SBP-domain like protein 13) could be putatively regulated by small RNA pab-siR156c. PaSPB13
mRNA had significant differences in expression between
WE and CE for day 20 samples from seedlings grown under
SD only. Under SD20 conditions, a significant decrease in
the transcript abundance of pab-miR156c coincided with
accumulation of PaSPB13 transcripts, while nonsignificant
differences in miRNAs transcript levels correspond to
nonsignificant differences in mRNA levels under other
conditions (Fig. 3).
Discussion
It is well known that miRNAs play an important role in regulating a variety of biological processes. The regulation
mechanisms include repression of translation and cleavage
of targeted mRNAs (Carthew & Sontheimer, 2009). The
miRNAs may directly target transcription factors which
affect plant development, and specific genes which control
metabolism. Many mature miRNAs are evolutionarily conserved in the plant kingdom, which provides a powerful
approach to predict the existence of miRNA orthologues in
other plants (Carthew & Sontheimer, 2009; Zhang et al.,
2009).
(a)
Fig. 3 Expression of conserved microRNA
(MiRNA) and novel miR100n (a) and their
putative targeted mRNAs (genes)(b) in
Norway spruce family 6 samples originated
after embryogenesis in cold (CE) and warm
(WE) environment at long day (LD) and after
6 and 20 d of short day (SD) treatment using
relative RT-PCR. Expression level of mRNAs
was measured as the difference between
PaAct (endogenous control) and the chosen
transcripts relative to the mean value for the
target genes. Bars indicate standard error of
means. Transcript levels of miRNAs were
normalized to geometric mean for three
selected ribosomal and transport RNA genes
(Pa4.5S, Pa5S and PatRNA-R).
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(b)
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One of the challenges in the study of plant miRNAs is to
identify novel miRNAs. For wooden plants with very long
generation times and limited genome sequence information, such as most conifer tree species, direct isolation,
cloning, and transcript sequencing and similarity search
among known ESTs, are currently the best alternative
methods for miRNA discovery. We aimed to identify
Norway spruce miRNAs that were differentially expressed
in full-sib progenies from two families, where one expressed
the epigenetic memory and the other did not. In this way
we hoped to identify the most pertinent candidates, which
could act in the adaptive epigenetic memory mechanism
affecting the bud phenology and frost hardiness of Norway
spruce (Johnsen et al., 2005a,b; Kvaalen & Johnsen, 2008).
Toour knowledge, our report is the first one dealing with
miRNAs in spruce.
The small RNAs were isolated and sequenced from two
libraries. In total, we obtained 199 distinct small RNA
sequences. The length distribution of small RNA sequences
showed the absolute prevalence of 21 nt small RNAs; considerably less well represented were the 22 nt small RNAs
and the occurrence of the 24 nt length small RNAs was
rare. This distribution has been shown for gymnosperms
(Dolgosheina et al., 2008). Search at the miRBase revealed
just four conserved miRNA, which could be categorized as
orthologues of the loblolly pine pta-miR159a, miR949,
miR951 and rice osa-miR529b miRNA genes, suggesting
that our Norway spruce small RNA collection likely
includes novel miRNAs not previously described. However,
for three conserved miRNAs homologous to pta-miR159a
(pab-miR159a), miR949 (pab-miR037) and osa-miR529b
(pab-miR038), we could not confirm precursor with hairpin structure among available spruce ESTs. We suspect that
these miRNAs could originate from introns of genes and
be expressed during mRNA maturation (Carthew &
Sontheimer, 2009). We had similar results when analysing
the reference set of miRNA sequences from other species.
The ESTs of miRNA genes could not be found, and neither
did we manage to confirm hairpin folding patterns for 42
from 60 conserved miRNAs that we found to be homologous to sequences in the spruce EST Database. Thus, EST
collections were not the only source for the miRNAs search
because they could only help us to identify miRNAs originated from exons, together with expressed product, or from
3¢ UTR (Bartel, 2004; Axtell & Bowman, 2008). Full
genome sequence of any of the spruce species will promote considerably the discovery and confirmation of miRNAs. Based on
our data we anticipate that part of the novel small RNAs
obtained could also be confirmed as miRNAs in the future.
We identified stem–loop precursor structures for 25
novel small RNAs and 17 conserved miRNAs, which met
all the criteria listed, and these were designated as true
miRNAs. Three small RNAs were assigned as miRNAs
based on homology to conserved miRNAs. All ESTs that
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coded for miRNA genes were homologous to unknown
genes. This indicates that a large portion of such kind of
ESTs, with no significant similarities in the Databases,
could be an excellent source for identifying new miRNA
genes in future research.
We consider that direct cloning and sequencing, with the
construction of concatemerized small RNA libraries, is a
promising avenue for identifying new miRNAs. We
sequenced only a very limited number of clones (328) from
WEL and CEL, but still we obtained quite large number of
distinct small RNAs (193), from which we further identified
24 novel and 4 conserved miRNAs. These became founders
of 20 miRNA families. Contemporary next-generation
sequence approaches will greatly facilitate the identification
of new miRNAs. In particular, such sequencing would
allow changes in small RNA expression levels to be monitored by the sequencing process itself, greatly speeding up
the discovery of small RNAs that change expression owing
to developmental condition.
The lack of conserved miRNAs among sequences we
found could indicate novel elements specifically associated
with ‘epigenetic memory’ regulation, which in turn could
affect developmental processes in Norway spruce. Perhaps
they also could serve as a source for novel epigenetic elements in general, and these newly identified miRNAs will
be studied further by us to find their target genes and their
functions. In the absence of the full transcriptome and genome sequence for spruce, the microRNA genes reported
here likely represent an important part of the genes that
produced the mature miRNAs but probably there is a
significantly larger number of such genes present in this
species, but not in the EST collections available.
Identification of miRNA target genes has been a great
challenge. Currently, there is no clear consensus as to what
criteria we should follow to determine miRNA targets and
to confirm their biological efficacy (Kuhn et al., 2008). For
plants, miRNAs are not strictly located at 3¢ UTR, but
could be placed in UTRs, exons and nontranscribed part of
the genome (Fahlgren et al., 2007; Carthew & Sontheimer,
2009). Most of the miRNAs have, however, been shown to
be nearly perfectly complementary to their targets (Meyers
et al., 2006). Thus, we used a computational approach for
searching of putative targets, looking for matching sites at
the reverse strand of ESTs.
Unfortunately, we did not find target genes for most of
the novel and conserved miRNAs. In addition, a considerable amount of pab-miRNAs’ putative target genes were
unknown or without significant similarity to other genes at
the Databases. Lack of target genes for confirmed miRNAs
in the quite comprehensive spruce ESTs Database could
imply the existence of unknown and specific epigenetic regulation pathways, which implies a necessity to make specific
EST libraries related to the epigenetic memory regulation
transcriptomes.
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Another big share of miRNA target genes were homologous to TIR(CC) ⁄ NBS ⁄ LRR disease-resistance proteins,
which could play an important role in the plant defence system or possibly the extracellular domains of such proteins
could act as receptors for sensing other extracellular cues.
Moreover, from the 67 small RNAs with identified putative
target genes among the spruce ESTs, 12 distinct small
RNAs had exact matching to ESTs that were homologous
to different loblolly pine TIR(CC) ⁄ NBS ⁄ LRR diseaseresistance proteins. Disease resistance LRR genes could be
among the genes often targeted by miRNA genes. It is
shown for Brassica that miRNA genes can originate through
inverted duplication events from TIR-NBS-LRR diseaseresistance protein-coding gene sequences (He et al., 2008)
and participate in their regulation. Relatively small amount
of miRNAs were targeted to known structural genes and
transcription factors.
Relative real time RT-PCR was used to investigate the
expression of 24 novel and 21 conserved miRNAs in
Norway spruce seedlings originated after embryogenesis on
CE and WE of family F1 (having low ‘epigenetic memory’
response) and F6 (having high ‘epigenetic memory’
response) under LD conditions and after SD treatment,
which initiated growth cessation and bud set. As selection
criterion of miRNAs involvement into epigenetic regulation
we considered significant differences in transcript levels
between WE and CE originated samples of family 6 and
lack of differences in family 1 or vice versa.
We found several candidates between novel and
conserved miRNAs that correspond to our selection criterion.
The candidates among novel miRNAs were miRNAs pabmiR029, 080, 100, 105, 119, 122, 132, and 144a and b.
We found it interesting that pab-miR061 showed significant differences in transcript abundances at SD samples for
F1, but not for F6. Among the conserved miRNAs, the best
candidates were pab-miR156c, 159a, 160, 395, 396a,b,
535, 858, 947 and 951, despite the fact that we did not find
miRNA genes or did not have confirmed hairpin structure
for several of them (pab-miR156c, 159a, 858). The precise
roles of these candidate pab-miRNAs and their genetic
interactions with target transcripts in epigenetic regulation
of bud set need to be examined further.
For the most novel miRNAs, significant differences
between WE and CE origins (when detected) lasted until
day 20 after SD treatment. This could reflect the fact that we
used SD20 samples for constructing the miRNA libraries,
and mainly miRNAs that differentiated at SD20 were
cloned, or that some miRNAs regulate genes in the late SDresponse, reaching their high levels of accumulation or suppression > 6 days after SD treatment. Only pab-miR029
showed significant differences between both WE and CE
samples of F6 at SD6, and pab-miR144a were significantly
different both for SD6 and SD20. pab-miR144a targeted
hypothetical protein gene and should be studied further.
The Authors (2010)
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Research
We found only 12 miRNAs (including both novel and
conserved) that targeted genes with putative known function. For the conserved miRNAs, their target sites should
possibly also be conserved across different plant species. As
expected, the targets for conserved miRNAs in spruce were
similar or functionally related to previously validated plant
miRNA targets. For example, pab-miR397 could target
laccase and laccase precursor (Table S3). Laccase has also
been predicted to be the target of miR397 in Arabidopsis and
rice (Abdel-Ghany & Pilon, 2008; Xue et al., 2009). pabmiR160 targeted AUXIN RESPONSE FACTOR10, similar
to what was described in Arabidopsis (Liu et al., 2007),
and pab-miR173 targeted PaAGO1 and pab-miR396a
targeted PaGRF, which was also known from studies with
Arabidopsis (Montgomery et al., 2008; Liu et al., 2009).
Putative targets were also predicted for some newly identified miRNAs. We used antagonistic presentation of
miRNA-mRNA transcript abundances, but should mention
that these observations are not an absolute measure as other
RISC (RNA-Induced Silencing Complex) components and
family members with different sequences may come to play
for actual regulation. We showed that pab-miR159a, orthologous to pta-miR159a, likely regulates expression of
PaGaMYB in Norway spruce. The GaMYB gene could
respond to GA signals and thus bei involved in GA transduction pathways, participating in numerous developmental
processes, including seed germination (Tsuji et al., 2006;
Gong & Bewley, 2008) and flower development (Achard
et al. 2004; Tsuji et al., 2006). miR159 is a conserved
miRNA family (Allen et al., 2007). miR159 is a phytohormonally regulated homeostatic modulator of GAMYB activity,
and hence of GAMYB-dependent developmental processes
(Achard et al., 2004; Millar & Gubler, 2005; Tsuji et al.,
2006; Allen et al., 2007). Further studies of pabmiR159a ⁄ miR159a and PaGaMYB involvement in the epigenetic regulation of development should be conducted,
along with measurements of GA regulation in relation to
growth cessation (Olsen et al., 1997).
Another spruce gene homolog, which is likely regulated
by miRNA is PaSPB13. SQUAMOSA promoter-binding
proteins (SBP) is a family of transcription factors possessing
a SBP-domain, which plays important roles in plant
development, including regulation of shoots development
and floral transition. The SBP genes are targeted by the
highly similar miRNAs miR156 and miR157 (Wu &
Poethig, 2006; Gandikota et al., 2007; Riese et al., 2007).
Our results generally confirm miRNA (pab-miR156c) targeted regulation of PaSPB13 gene expression. Putative participation of these transcription factors and pab-miR156c
may be involved in the regulation of the epigenetic memory
Norway spruce, as has been described for tomato (Manning
et al., 2006). pab-miR100 could regulate the expression of
PaSPT4. SPT4 is a transcription elongation factor, which
affects elongation by Pol II and influences growth and
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rRNA synthesis rates (Schneider et al., 2006). We found
significant accumulation of PaSPT4 transcripts from SD 6
to SD20 in WE spruce seedlings of family 6 and drastic
decrease of pab-miR100 transcript abundance, but no
PaSPT4-transcript changes in CE spruce seedlings of family
6 and family 1. Thus, this gene and the regulatory pabmiRNA expression patterns are consistent with a putative
involvement in epigenetic developmental regulation.
We expected that the expression of another MYB transcription factors could be regulated by miRNAs. The
miR159 family miRNAs have been described as regulators
of MYB factor genes in Arabidopsis (Reyes & Chua, 2007),
and miR399 in bean roots (Valdés-López et al., 2008).
Some lack of interrelation between transcript abundance of
miRNA858 and the targeted PaMyb10 gene could possibly
be caused by a delay between changes in small RNA
abundance and changing amounts of target mRNA transcript. Alternatively, in the case of post-transcriptional
repression instead of mRNA cleavage, there could appear to
be no direct interrelation. Despite some discrepancies, all
the chosen elements for deeper analysis of the miRNA–
mRNA pair, we found significant differences in transcript
abundances among WE and CE samples both for miRNAs
and mRNAs. Thus, we considered them as good candidates
for future studies in relation to the epigenetic memory
regulation.
There are still a great number of questions that remain to
be answered regarding Norway spruce miRNA functions
and targets, but our study demonstrates the existence of a
set of conserved miRNAs and a large proportion of novel
nonconserved miRNAs with relatively low expression levels.
Nearly all genes targeted by miRNA were unknown, so
unknown and hypothetical genes could be the main ‘players’ in epigenetic regulation. By analysing putative miRNA
target genes, we confirm the differential expression of several genes as a result or initiator of epigenetic regulation.
The miRNAs could also help us in finding the candidate
genes. A considerable proportion of the novel and conserved miRNAs were differentially expressed in relation to
whether the siblings originated from CE or WE. These
findings imply that both kinds of miRNA might be
involved or at least could be affected by the molecular
mechanisms that regulate the temperature-sensitive epigenetic memory. We believe that we are at the beginning of
a very important endeavour, where further studies of
miRNAs and their target genes will help us to acquire a
better understanding of this exciting phenomenon.
Acknowledgements
We thank Monica Fongen (Norwegian Forest and
Landscape Institute) for excellent technical help during small
RNA extraction and libraries construction. This work was
supported by the Norwegian Research Council (Grants #
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191455) and the Norwegian University of Life Sciences
(UMB).
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Supporting Information
Additional supporting information may be found in the
online version of this article.
Fig. S1 Averaged expression profiles of several ribosomal
and transport RNA genes as candidate to reference genes in
small RNA samples from Norway spruce progenies of
family 1 (F1) showing low ‘epigenetic memory’ response
and family 6 (F6), showing highest ‘epigenetic memory’
response.
Fig. S2 Predicted stem–loop structures of precursors containing the microRNA sequence, identified by using cloned
spruce small RNAs and conserved microRNA reference
sets.
Table S1 List of genes and primers for reverse-transcription
polymerase chain reaction (RT-PCR) analysed as reference
genes.
Table S2 Description of microRNA primers used for
reverse-transcription polymerase chain reaction (RT-PCR).
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Table S3 List of Norway spruce genes (mRNAs) studied putatively targeted by miRNAs and their primer
sequences.
Table S4 Isolation and identification of Norway spruce
small RNAs expressed in response to 20 d of SD treatment
in the progeny after embryogenesis in WE (WEL) and after
embryogenesis in CE (CEL).
Table S5 Precursor sequences for novel and conserved
microRNAs in Norway spruce.
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Table S6 List of conserved microRNAs from some other
plant species, which have matches among spruce expressed
sequence tags (ESTs) with unconfirmed stem–loop hairpin
precursor structures and their putative origin genes and ⁄ or
target genes (when found).
Please note: Wiley-Blackwell are not responsible for the
content or functionality of any supporting information
supplied by the authors. Any queries (other than missing
material) should be directed to the New Phytologist Central
Office.
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