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ORIGINAL PAPER
EST analysis and annotation of transcripts derivedfrom a trichome-specific cDNA library from Salvia fruticosa
Fani M. Chatzopoulou • Antonios M. Makris •
Anagnostis Argiriou • Jorg Degenhardt •
Angelos K. Kanellis
Received: 26 January 2010 / Revised: 24 February 2010 / Accepted: 2 March 2010 / Published online: 24 March 2010
� Springer-Verlag 2010
Abstract Greek sage (Salvia fruticosa Mill., Syn. Salvia
triloba L.) is appreciated for its essential oil which is used
as an aromatic spice and active against a wide range of
microorganisms and viruses. The essential oil is dominated
by terpenoids and flavonoids which are produced and
stored in glandular trichomes on the plant surface. The
present study aims to give insights into the metabolic
activities of S. fruticosa trichomes on a transcriptome level.
A total of 2,304 clones were sequenced from a cDNA
library from leaves’ trichomes of S. fruticosa. Exclusion of
sequences shorter than 100 bp resulted in 1,615 high-
quality ESTs with a mean length of 592 bp. Cluster
analysis indicated the presence of 197 contigs (908 clones)
and 707 singletons, generating a total of 904 unique
sequences. Of the 904 unique ESTs, 628 (69.5%) had
significant hits in the non-redundant protein database and
were annotated. A total of 517 (82.3%) sequences were
functionally classified using the gene ontologies (GO) and
established pathway associations to 220 (24.3%) sequences
in Kyoto encyclopedia of genes and genomes (KEGG). In
addition, 52 (5.8%) of the unique ESTs revealed a GO
biological term with relation to terpenoid (78 ESTs), phe-
nylpropanoid (43 ESTs), flavonoid (18 ESTs) or alkaloid
(10 ESTs) biosynthesis or to P450s (26 ESTs). Expression
analysis of a selected set of genes known to be involved in
the pathways of secondary metabolite synthesis showed
higher expression levels in trichomes, validating the tissue
specificity of the analyzed glandular trichome library.
Keywords Salvia fruticosa � Greek sage � EST analysis �Plant trichomes � Secondary metabolism � Gene expression
Introduction
Greek sage (Salvia fruticosa Mill.), also known as S. triloba
L., belongs to the Lamiaceae family. This family includes
important herbs, such as mint, basil, oregano, rosemary,
savory and lavender, which are known for their aromatic
and therapeutic properties since ancient times. S. fruticosa
is endemic in the Eastern Mediterranean and is used as
herbal tea as well as in the fragrance and pharmaceutical
industry (Rivera et al. 1994). Plant extracts such as its
essential oil constituents have been used in a wide range of
studies and showing hypoglycemic activity (Perfumi et al.
1991; Yaniv et al. 1987), cholinergic activity (Savelev et al.
2004), antimycotic activity (Abou-Jawdah et al. 2002),
Communicated by J. R. Liu.
Electronic supplementary material The online version of thisarticle (doi:10.1007/s00299-010-0841-9) contains supplementarymaterial, which is available to authorized users.
F. M. Chatzopoulou � A. K. Kanellis (&)
Group of Biotechnology of Pharmaceutical Plants,
Laboratory of Pharmacognosy,
Department of Pharmaceutical Sciences,
Aristotle University of Thessaloniki,
541 24 Thessaloniki, Greece
e-mail: kanellis@pharm.auth.gr
A. M. Makris
Department of Natural Products,
Mediterranean Agronomic Institute of Chania,
PO Box 85, 731 00 Chania, Crete, Greece
J. Degenhardt
Institute for Pharmacy, Martin Luther University
Halle-Wittenberg, Hoher Weg 8, 06120 Halle, Germany
A. M. Makris � A. Argiriou
Institute of Agrobiotechnology,
Center for Research and Technology, Hellas,
6th Km Charilaou Thermi Rd, 570 01 Thermi, Greece
123
Plant Cell Rep (2010) 29:523–534
DOI 10.1007/s00299-010-0841-9
antifungal activity against several human or plant pathogens
(Adam et al. 1998; Ali-Shtayeh and Abu Ghdeib 1999;
Daferera et al. 2000; Pitarokili et al. 2003; Sokovic et al.
2002), as well as anti-inflammatory, antimicrobial, antiviral
and cytotoxic activities (Kaileh et al. 2007; Longaray
Delamare et al. 2007; Sivropoulou et al. 1997). Furthermore,
the occurrence of phenolic compounds in the essential oil of
S. fruticosa is responsible for its anti-oxidative properties
(Exarchou et al. 2002; Matsingou et al. 2003; Ozcan 2003;
Papageorgiou et al. 2008; Pizzale et al. 2002).
The production, storage and secretion of the essential oil
takes place in unbranched epidermal appendages, called
glandular trichomes. All the aerial parts of S. fruticosa are
covered with trichomes, but their density is higher in young
leaves and at the lower leaf surface (Karousou et al. 2000).
Although the chemical composition of its essential oil can
vary depending on the season (Papageorgiou et al. 2008)
and the genetic diversity within the species (Bellomaria
et al. 1992; Pitarokili et al. 2003; Skoula et al. 2000), its
main components found in different studies are oxygenated
monoterpenes (1,8-cineole, camphor, borneol), monoter-
pene hydrocarbons (a-pinene, b-pinene, myrcene, camph-
ene), sesquiterpene hydrocarbons (b-caryophyllene) and
small amounts of diterpenes (manool and labd-7,13-dien-
15-ol) (Karioti et al. 2003; Langer et al. 1996; Papageor-
giou et al. 2008; Pitarokili et al. 2003; Putievsky et al.
1986; Skoula et al. 2000). Apart from terpenoids, other
secondary metabolites like phenylpropanoids (Gang et al.
2001) or flavonoids (Aziz et al. 2005) can accumulate in
the trichomes of different species. The functional roles of
secondary metabolites in trichomes include defence against
pathogens (Friedman et al. 2002), resistance to herbivores
(Chermenskaya et al. 2001; Mauricio and Rausher 1997)
and attraction of pollinators (Koeduka et al. 2006).
The biological and economical significance of second-
ary metabolites in glandular trichomes warrants the study
of their biosynthesis. For the biotechnological production
of a desirable compound in large scale or in a host species,
it is necessary to identify the genes participating in its
biosynthesis. A useful tool in that direction is the con-
struction of a cDNA library of the tissue producing the
compound of interest. In the last decade, a number of
cDNA libraries from glandular trichomes of different
species, for instance hop (Nagel et al. 2008; Wang et al.
2008), Cistus creticus (Falara et al. 2008), Artemisia annua
(Bertea et al. 2006), alfalfa (Aziz et al. 2005), tomato
(Fridman et al. 2005), Salvia stenophylla (Hoelscher et al.
2003), basil (Gang et al. 2001) and peppermint (Lange
et al. 2000), have been constructed and led to the identi-
fication of several genes participating in biosynthesis of
important secondary metabolites. To that end, we report
the analysis of a glandular trichomes cDNA library from
S. fruticosa in order to identify putative genes that are
involved in secondary metabolism pathways and especially
in terpenoid biosynthesis.
Materials and methods
Plant material
Glandular trichomes were isolated from young leaves using
a method modified from Gershenzon et al. (1992). In brief,
approx. 7 g of young, not fully expanded leaves were
harvested, soaked in ice-cold, distilled water containing
0.05% Tween 20 for 2 h. The water was then decanted and
the leaves were washed twice with ice-cold, distilled water,
and abraded using a cell disrupter (Bead Beater, Biospec
Products, Bartlesville, USA). The chamber was filled with
the plant material, 65 ml of glass beads (0.5–1.0 mm
diameter), XAD-4 resin (1 g/g plant material), and ice-cold
extraction buffer [25 mM HEPES pH 7.3, 12 mM KCl,
5 mM MgCl2, 0.5 mM K2HPO4, 0.1 mM Na4P2O7, 5 mM
DTT, 2.4 g l-1 sucrose, 26.4 g l-1D-sorbitol, 6 g l-1
methyl cellulose, and 10 g l-1 polyvinylpyrrolidone (PVP;
Mr 40,000)] to full volume. Glands were abraded from the
leaves with three pulses of 1 min at medium speed, with a
1-min rest between pulses. Following abrasion, the glands
were separated from leaf material, glass beads, and XAD-4
resin by passing the supernatant of the chamber through a
500-lm mesh cloth. The residual plant material and beads
were rinsed twice with 10 ml ice-cold isolation buffer
(extraction buffer without methylcellulose) and passed
through the 500-lm mesh. The combined 500-lm filtrates
were then consecutively filtered through membranes with
decreasing mesh size (350, 200, and 100 lm). Finally,
clusters of secretory cells (approx. 60 lm in diameter)
were collected by passing the 100-lm filtrate through a 20-
lm mesh. An aliquot of the isolated cell clusters were
checked for integrity and purity with a light-optical
microscope before being transferred to a 1.5 ml reaction
tube and frozen in liquid nitrogen prior to RNA extraction.
RNA isolation, cDNA library construction and EST
sequencing
Total RNA was extracted with Trizol in accordance to the
manufacturer’s instructions. The cDNA was prepared with
‘‘SMART’’ cDNA synthesis kit (Clontech) and was ligated
to the pDNRLib vector in the SfiIA and SfiIB restriction
sites. The single pass sequencing of 2,304 ESTs (using the
T7 primer) was carried out by the Purdue Genomics Core
Facility of the University of Purdue. The reads were then
processed (poly-A trimming and vector trimming) using
the pipeline Lucy (Chou and Holmes 2002) resulting in
1,615 high-quality sequences ([100 bases).
524 Plant Cell Rep (2010) 29:523–534
123
Contig assembly and sequence analysis
High-quality ESTs (1,615 sequences) were used for
assembling into clusters. The analysis was performed using
the Contig Assembly Program CAP3 (Huang and Madan
1999) (http://mobyle.pasteur.fr/cgi-bin/MobylePortal/portal.
py?form=cap3) using default parameters. The resulting
unique ESTs (contigs and singletons) were then imported
into the bioinformatics tool Blast2GO (Conesa et al. 2005)
(http://www.blast2go.de/) and were compared against the
National Center for Biotechnology Information (NCBI)
non-redundant protein database BLASTX (E value \ 10-3)
(Altschul et al. 1997).
Furthermore, in order to identify similar sequences in
other trichome containing plant species, all ESTs were
compared against trichome-specific databases. Sequences
were downloaded from the TrichOME Database (http://
www.planttrichome.org/) and local BLAST searches were
performed.
Open reading frames (ORFs) were predicted by Orf-
Predictor (Min et al. 2005) (https://fungalgenome.concordia.
ca/tools/OrfPredictor.html). It should be noted that this site
has been recently moved to a new web address (http://
proteomics.ysu.edu/tools/OrfPredictor.html). The GC con-
tent of the ESTs was estimated using geecee provided
by the Institut Pasteur (http://mobyle.pasteur.fr/cgi-bin/
MobylePortal/portal.py?form=geecee). Signal peptides for
the subcellular localization of the predicted proteins were
identified using the software TargetP (Emanuelsson et al.
2000) (http://www.cbs.dtu.dk/services/TargetP/). TargetP
was used only for the full-length sequences or for those who
predicted to contain the N-terminal according to manual
BLASTX search. Its prognosis is based on the presence or
absent of secretory pathway signal peptide, chloroplast
transit peptide or finally mitochondrial targeting peptide.
In order to assign a putative function to the proteins, we
used the Blast2GO tool. The mapping and annotation of
the sequences according to gene ontology (GO) terms
(Ashburner et al. 2000) is based on sequence similarity and
therefore, sequences without BLAST hit were not anno-
tated. For the annotation configuration the default settings
were used (E value filter of 1E-6 and annotation cutoff of
55). Each sequence could have more than one GO terms,
either at the different GO categories (Biological Process,
Molecular Function and Cellular Component) or at the
same category. Furthermore, in order to improve annotat-
ability we used InterProScan, which searched the databases
BlastProDom, FPrintScan, HMMPIR, HMMPfam, HMM-
Smart, HMMTigr, ProfileScan, ScanRegExp and Super-
Family (Quevillon et al. 2005) (http://www.ebi.ac.uk/
interpro/index.html) provided by the EBI (Labarga et al.
2007) (http://www.ebi.ac.uk/) through Blast2GO. The
sequences are mapped according to their domain/motif
similarity and the GO results can be merged with the
remaining annotations. Furthermore, the assignment of the
peptides into metabolic pathways was done by the Kyoto
Encyclopedia of Genes and Genomes (KEGG, http://www.
genome.jp/kegg/kegg2.html).
Expression analysis
Total RNA from young and old leaves, glandular trichomes
and the remaining part of the leaves was extracted as
described. One microgram of total RNA from each tissue
was used in a reverse transcription reaction using 0.5 lg
30RACE Adapter Primer and SuperScript III-RT (Invitro-
gen, Carlsbad, CA, USA) following the manufacturer’s
protocol. Successful cDNA synthesis was monitored by
amplifying a fragment of the eIF4a gene. PCR was per-
formed using the Platinum SYBR Green qPCR SuperMix-
UDG (Invitrogen, Carlsbad, CA, USA) with 1/20 of the
synthesized cDNAs as template and the corresponding
primers at 0.4 lM. The cycling conditions were: 2 min/
50�C, 2 min/94�C, 40 cycles of 15 s/94�C, 20 s/58�C,
20 s/72�C and a final extension step of 10 min/72�C. The
primers used for the expression experiments are indicated
in Table 1S. Two different housekeeping genes to be used
as controls for the cDNA quantity, GAPDH and eIF4a,
were tested. The eIF4a presented more stable expression
levels in all the examined tissues and was used as internal
control for cDNA normalization in the expression analysis.
Quantitative expression analysis of the genes was per-
formed in a real-time PCR, using the RG6000 (Corbett Life
Science, Sydney, AU) Real-Time PCR system. For identi-
fication of the PCR products a melting curve was performed
from 65 to 95�C with read every 0.2�C and 5 s hold between
reads. The whole experimental procedure was performed at
least three times starting from cDNA synthesis. The thresh-
old cycle (Ct) values of the triplicate PCRs were averaged
and relative quantification of the transcript levels was per-
formed using the comparative Ct method (Livak and Sch-
mittgen 2001). The fold change in the target gene was
determined with the following formula: fold change =
E-DDCT, where DDCT = (Ct target gene - Ct Ref) at Point
X - (Ct target gene - Ct Ref) Point Y and E the efficiency
of the reaction calculated using the LinRegPCR software
(Ramakers et al. 2003). The results were expressed as rela-
tive values to the gene expression levels in leaves.
Results and discussion
Generation of ESTs and contig assembly
A total of 2,304 clones were sequenced from a cDNA
library constructed from total leaf trichome total RNA of
Plant Cell Rep (2010) 29:523–534 525
123
S. fruticosa. Using the vector/quality clipping program
Lucy (Chou and Holmes 2002), clones with no insert or
sequences shorter than 100 bp were excluded, resulting in
1,615 high-quality ESTs with a mean length of 592 bp
(Table 1) (Fig. 1S). All edited EST sequences have been
submitted to the GenBank dbEST and are accessible under
the accession numbers from FE535951 to FE537409.
Cluster analysis with CAP3 (Huang and Madan 1999)
indicated the presence of 197 contigs consisting of 908
ESTs and 707 singletons. The transcript redundancy of the
EST library was 56% (number of clustered ESTs/total
ESTs), that means that the gene discovery rate was 44%.
According to the clustering, a total of 904 unique
sequences (UniESTs) were identified (Table 1), of which
878 (97%) had open reading frames (ORFs) (data not
shown). The GC content distribution of the coding
sequences is presented in Fig. 1 with an average GC con-
tent of about 43%.
The most highly expressed ESTs (C10 ESTs) are ranked
according to the number of contributing ESTs (Table 2).
The abundance of these ESTs suggests an important role of
their transcripts in the metabolism of these tissues. Seven
of them were detected over 1% of the total sequences. Of
these, the most numerous cluster was 94, which is com-
posed of 71 ESTs and bears homology to a non-specific
lipid transfer protein (LTPs) precursor (Table 2). Plant
LTPs transfer phospholipids as well as glycolipids, fatty
acids and sterols across membranes (Guerbette et al. 1999;
Kader et al. 1984). Other functions for LTPs have been
proposed, such as participation in the protection against
pathogens and the wax or cutin deposition in the cell walls
of expanding epidermal cells and certain secretory tissues
(Lange et al. 2000; Maldonado et al. 2002; Pyee et al.
1994; Regente and De La Canal 2003; Sterk et al. 1991).
Plant trichomes are rich in LTPs as judged by the EST
analysis of a number of trichome-specific cDNA libraries
such as hop (Wang et al. 2008), Cistus creticus (Falara
et al. 2008), alfalfa (Aziz et al. 2005), basil (Gang et al.
2001) and peppermint (Lange et al. 2000). The increased
presence of LTP transcripts in the leaf trichome cDNA
library of S. fruticosa indicates its involvement in plant
defence (Maldonado et al. 2002; Molina et al. 1993). This
hypothesis is also supported by the higher expression in
trichomes of a S. fruticosa LTP (GenBank: FE537054)
(Fig. 4). The second most abundant cluster was the 151
with 60 ESTs (Table 2). This cluster revealed homology to
a hypothetical protein (NitaMp027) from Nicotiana taba-
cum with unknown function (Sugiyama et al. 2005).
However, most of the remaining contigs contain 2 or 3
ESTs, a reflection of an effective representation of genes
with low abundance within the library (Fig. 2S). The
redundancy of the clusters is similar to other trichomes’
cDNA libraries recently evaluated (Falara et al. 2008;
Lange et al. 2000).
Among the most abundant ESTs, several secondary
metabolism-related ESTs were identified (Table 2). More
specifically, clusters 14, 53 and 180 reveal homology to
phenylcoumaran benzylic ether reductase homolog Fi1
(PCBER), germacrene D synthase and caffeic acid 3-O-
methyltransferase (COMT), respectively (Table 2).
PCBERs are involved in lignan biosynthesis, which play an
important role in plant defence (Gang et al. 1999; Min et al.
2003; Vander Mijnsbrugge et al. 2000), while COMT is a
key enzyme in lignin and flavonoid biosynthesis which
converts caffeic acid to ferulic acid or 5-hydroxyferulate to
sinapate (Anterola and Lewis 2002; Guo et al. 2001).
COMT is induced by mechanical wounding and water
stress, but it is not affected by insect feeding (Reymond
et al. 2000). Germacrene D synthase catalyzes the forma-
tion of germacrene D from farnesyl diphosphate (FPP)
(Dudareva and Pichersky 2006) and it was recently found
to exhibit a trichome-specific expression (Falara et al.
2008). Germacrene D is a sesquiterpene abundant in many
essential oils (Flamini et al. 2007; Ogutcu et al. 2008;
Pitarokili et al. 2002). As germacrene D is a volatile
hydrocarbon, it contributes to plant scents (Guterman et al.
2002) and can play a significant role in the attraction of
pollinating insects (Buttery et al. 1986; MacFarlane et al.
2003). In addition, a monoterpene synthase (cluster 61)
Table 1 Summary statistics of the ESTs generated from leaves’
trichomes of Salvia fruticosa
Feature Value
Total number of clones sequenced 2,304
Number of high-quality sequences 1,615 (70%)
Average length of high-quality ESTs (bp) 592 ± 5.8
Number of contigs 197
Number of ESTs in contigs 908 (56%)
Number of singletons 707 (44%)
Number of UniESTs 904
Fig. 1 GC content distribution. The GC content of each UniEST is
plotted against their abundance (average GC content = 42.5%)
526 Plant Cell Rep (2010) 29:523–534
123
with high similarity to a S. fruticosa cineole synthase
(SfCinS1) has been identified (Kampranis et al. 2007). 1,8-
Cineole synthase was found to be either a single product
enzyme (Shimada et al. 2005) or a multi-product enzyme
that forms of a terpenoid mixture with 1,8-cineole being
the major product (Kampranis et al. 2007; Roeder et al.
2007; Wise et al. 1998). With up to 74% of the total
content, this monoterpene was the dominant component in
the essential oil (Karousou et al. 2000; Langer et al. 1996;
Papageorgiou et al. 2008; Putievsky et al. 1986; Sivro-
poulou et al. 1997; Skoula et al. 2000, 1999; Sokovic et al.
2002) and showed antifungal (Pitarokili et al. 2003;
Sokovic et al. 2002), antimicrobial and antiviral activity
(Sivropoulou et al. 1997).
In order to ascribe a putative function to each unique
EST, a similarity search against the NCBI non-redundant
protein database BLASTX (E value \ 10-3) (Altschul
et al. 1997) using the Blast2GO analysis tool (Conesa et al.
2005) was performed. Of the 904 unique ESTs, 628
(69.5%) revealed at least one significant match, while the
remaining 276 had no significant similarity (26.9%) or
were similar to unknown proteins (3.6%). The majority of
the annotated sequences had top BLAST hits to transcripts
from Oryza sativa (20%), followed by Arabidopsis thali-
ana (16%) and Vitis vinifera (14%) (Fig. 3S). Taxonomi-
cally, the vast majority of the top BLAST hits belonged to
the asterids subclass (64%) which includes the Solanaceae
and Lamiaceae families. Two other subclasses, namely
rosids (24%; Fabaceae, Brassicaceae and Salicaceae) and
commelinids (12%; Poaceae and Arecaceae), were less
represented.
Putative subcellular localization
The amino acid sequences of the full-length UniESTs or
those who had the N-terminus were used for the prediction
of the subcellular localization of the proteins. The analysis
was performed using the software TargetP (Emanuelsson
et al. 2000). Of the 239 sequences analyzed, 38 (15.9%)
contained secretory pathway signal peptide, 33 (13.8%)
contained a chloroplast transit peptide and 27 (11.3%)
contained a mitochondrial targeting peptide, while for the
remaining sequences (141, 58.9%) no prediction was
available (Table 2S).
Functional analysis of the unigenes
Gene ontology annotation
Of the 904 UniESTs, 628 (69.5%) had significant hits in
the non-redundant protein database and were annotated in
order to retrieve a putative function. A total of 517
(82.3%) unique sequences were functionally classified in
one or more ontologies [GO categories: biological process
(P), molecular function (F) and cellular component (C)]
(Ashburner et al. 2000) (Fig. 4S). For the functional
annotation, the automated software Blast2GO was used.
However, it must be taken into account that many
Table 2 The most abundant ESTs detected from the sequencing
Cluster ID No. of ESTs/
contig
Description from nr hit (BlastX) % identity E value % of total
ESTs
94 71 Non-specific lipid transfer protein precursor (Fragaria 9 ananassa) 53 1E-19 4.40
151 60 Hypothetical protein NitaMp027 (Nicotiana tabacum) 98 2E-41 3.72
47 38 H ? -transporting two-sector ATPase chain 9.1 (Raphanus sativus) 91 3E-09 2.35
58 38 No significant similarity – – 2.35
14 24 Phenylcoumaran benzylic ether reductase homolog Fi1
(Forsythia 9 intermedia)
73 7E-122 1.49
68 23 Putative stress-responsive protein [Oryza sativa(japonica cultivar-group)]
50 4E-21 1.42
86 17 No significant similarity – – 1.05
37 15 Unknown protein (Vitis vinifera) 42 5E-22 0.93
69 15 Cytochrome P450 monooxygenase isoform I (Sesamum indicum) 48 4E-69 0.93
53 13 Germacrene D synthase (Ocimum basilicum) 53 1E-163 0.80
111 12 Pathogenesis-related protein 10 (Vitis vinifera) 60 1E-51 0.74
61 12 Cineole synthase (Salvia fruticosa) 99 0.0 0.74
3 11 Unknown protein (Arabidopsis thaliana) 25 0.005 0.68
159 10 ATPase subunit 1 (Beta vulgaris subsp. vulgaris) 95 0.0 0.62
180 10 Caffeic acid 3-O-methyltransferase (Catharanthus roseus) 64 1E-58 0.62
Contigs with more than 10 EST members are presented
Plant Cell Rep (2010) 29:523–534 527
123
sequences had more than one assignment within a GO
category, resulted in 1,915 GO terms in total and at a
mean GO level of 4.92 (Fig. 5S).
In the biological class (second level GO terms, Fig. 2a)
the majority of the GO terms were grouped into two cate-
gories, namely, cellular (GO:0009987, 32%) and metabolic
(GO:0008152, 31%) processes. The secondary metabolite
processes were included in metabolic processes (third level
GO terms) and represented the 1.2% of the GO terms on that
level (data not shown). Considering the molecular function
class (second level GO terms, Fig. 2b), the vast majority
were involved in the catalytic activity (GO:0003824, 40%)
and the binding activity (GO:0005488, 39%). Furthermore,
for the cellular component class (second level GO terms,
Fig. 2c) the assignments were mostly given to cell
(GO:0005623, 29%), cell part (GO:0044464, 29%) and
organelle (GO:0043226, 23%).
Annotation augmentation using InterProScan
The number of the Blast-based annotated sequences with
GO terms can be increased using InterProScan (Quevillon
et al. 2005). The search for additional databases for motif/
domain similarities resulted in 132 new annotations (2,047
in total) with a slight difference in the mean GO level
(4.90). The most common InterPro families are presented
in Table 3. There are 422 InterPro families recognized,
with the most frequent family being the NAD(P)-binding
with 11 members, followed by the thioredoxin fold
(9 members). The terpene synthase, metal-binding and the
terpenoid synthase families consist of 7 and 6 members,
respectively (Table 3).
Pathway analysis
For the establishment of pathway association, the Kyoto
Encyclopedia of Genes and Genomes (KEGG) within
Blast2GO were used. The mapping process of GO terms
allows the recovery of the Enzyme Commission numbers
(EC number) and their classification in KEGG pathways. A
total of 220 (24.3%) UniESTs disposed one or more EC
numbers providing 263 ECs. These EC numbers were
mapped to 121 KEGG pathways (Table 3S). The 25 most
represented pathways (C7 UniESTs) are presented in
Table 4. Among the metabolic pathways identified, six
secondary metabolism-related pathways were included and
concerned terpenoid (ko00900), monoterpenoid (ko00902),
phenylpropanoid (ko00940), flavonoid (ko00941) and
alkaloid I (ko00950) and II biosynthesis (ko0090) (Table 5).
Five enzymes participating either in the cytosolic (MVA
pathway), or in the plastidic (MEP pathway) terpenoid bio-
synthesis pathways have been mapped into two KEGG
pathway categories, namely terpene biosynthesis and
especially monoterpene biosynthesis pathways (Table 5).
Several other enzymes contributing to phenylpropanoid,
flavonoid and alkaloid biosynthesis have been recognized
(Table 5).
Genes participating in biosynthesis of secondary
metabolites in Salvia fruticosa leaf trichomes
The trichomes of S. fruticosa are the ‘‘factories’’ where the
biosynthesis of a wide range of secondary metabolites,
such as terpenoids (mono-, di- and sesqui-terpenoids),
flavonoids and phenylpropanoids takes place (Exarchou
et al. 2002; Karousou et al. 2000; Pizzale et al. 2002;
Sivropoulou et al. 1997). Although a number of alkaloids
have been isolated from roots of Salvia species, like
S. yunnanensis and S. prionitis (Li et al. 2000; Lin et al.
2006), there is no references for their presence in S. fruti-
cosa essential oil. The presence of transcript of putative
alkaloid biosynthesis enzymes needs further investigation.
The cDNAs of these genes will provide a useful tool for the
elucidation and genetic manipulation of the pathways.
Several sequences in the trichomes EST library of
S. fruticosa revealed homology to genes participating in
biosynthesis of secondary metabolites. A complete list of
the putative genes is presented in Table 4S. Most of the
secondary metabolism-related ESTs had high similarity
with genes from the terpenoid biosynthetic pathway
(44.3%), followed by the phenylpropanoid pathway
(24.7%) (Table 4S). The genes contributing to flavonoid
and alkaloid biosynthesis represent the 10.3 and the 5.7%,
respectively. In addition, a number of putative P450s
(14.9%) that might participate in secondary metabolites’
biosynthesis have been recognized (Table 4S).
Concerning the terpenoid biosynthesis, genes partici-
pating in both the plastidic and cytosolic metabolic path-
ways have been identified (Table 4S). In particular,
nine out of ten genes (1-deoxyxylulose-5-phosphate syn-
thase, 1-deoxy-D-xylulose 5-phosphate reductoisomerase,
2-C-methyl-D-erythritol 4-phosphate cytidyltransferase,
4-diphosphocytidyl-2-C-methyl-D-erythritol kinase, 2C-
methyl-D-erythritol 2,4-cyclodiphosphate synthase, 1-hydroxy-
2-methyl-butenyl 4-diphosphate reductase, isopentenyl
pyrophosphate isomerase, geranyl diphosphate synthase
and geranylgeranyl diphosphate synthase) are involved in
the formation of the geranyl diphosphate and geranylger-
anyl diphosphate, the substrates of mono- and diterpene
biosynthases, respectively. Also identified in the trichome
library were several monoterpene synthases (cineole syn-
thase 1, cineole synthase 2, bornyl diphosphate synthase
homologue) and diterpene synthases (copalyldiphosphate
synthase, ent-kaurene synthase homologue) (Table 4S).
Furthermore, most of the genes (five out of eight) acting in
the cytosol for the biosynthesis of the sesquiterpene
528 Plant Cell Rep (2010) 29:523–534
123
precursor FPP have been recognized (acetoacetyl-
CoA thiolase, 3-hydroxy-3-methylglutaryl-CoA synthase,
3-hydroxy-3-methylglutaryl-CoA reductase, isopentenyl
pyrophosphate isomerase, farnesyl diphosphate synthase),
as well as some sesquiterpene synthases (germacrene D
synthases, cis-muuroladiene synthase) (Table 4S). A subset
Fig. 2 Gene Ontology (GO)
assignment (2nd level GO
terms) of 904 Salvia fruticosaannotated UniESTs using the
Blast2GO software. The three
GO categories, biological
process (a), molecular function
(b) and cellular component (c)
are presented
Plant Cell Rep (2010) 29:523–534 529
123
of six predicted genes involved in different predicted
metabolic pathways, was selected for expression analysis
(Figs. 3, 4).
To validate the tissue specificity of the analyzed
S. fruticosa glandular trichome library we selected a rep-
resentative set of genes for expression analysis using real-
time PCR. The EST of SfLTP (GenBank: FE537054)
identified as the most numerous gene encountered, the
monoterpene cineole synthase 1 encountered in 12 EST
SfCinSin1 (GenBank: DQ785793), the second cineole
synthase SfCinSin2 (GenBank: FJ618810) encountered in 2
EST, the monoterpene bornyl diphosphate synthase
homologue SfBPPS1 (GenBank: FE537328) with 4 EST,
the phenylcoumaran benzylic ether reductase homologue
Fi1 SfIFR (GenBank: GU479926) representing the most
abundant EST from the flavonoid biosynthetic pathway
with 24 EST identified and the triose-phosphate isomerase
homologue SfTPI (GenBank: FE536366) a core biosyn-
thetic gene. Two housekeeping genes were chosen as
controls for the cDNA quantity, the SfGAPDH (GenBank:
FE536708) and the SfeIF4a (GenBank: FE536666). Among
them, SfeIF4a was found to have the most stable expression
levels in all examined tissues and was subsequently
selected for normalization. Initially, the expression levels
of SfGAPDH, SfTPI and SfIFR were tested in old and
young leaves. The results indicated a lower expression of
approx. 25–30% in older leaves of all three genes
examined. Interestingly also the SfGAPDH presents a
decreased expression levels using eIF4a as internal control
(Fig. 3) probably due to a decrease of the overall metab-
olism in old leaves.
Quantitative expression analysis in whole leaves, iso-
lated trichomes and leaves without trichomes revealed a
higher expression of SfLTP, SfCinSin1, SfCinSin2,
SfBPPS1 and SfIFR in isolated trichomes compared to
leaves without trichomes or to whole leaves. More spe-
cifically, SfLTP showed a 20- to 25-fold induction, the
SfCinSin1, which is the main cineole synthase of Salvia
fruticosa exhibited[100-fold induction, the second cineole
synthase SfCinSin2 with [30-fold increase, the SfBPPS1
homologue with[30-fold induction and SfIFR with 18-fold
induction. No significant difference for SfTPI was detected
(Fig. 4). The expression data confirmed the tissue speci-
ficity of the library analyzed. Their relative transcript
abundance corresponds quite well with the number of EST
identified for each transcript but they are not identical. The
Table 3 The most frequent InterPro families found in Salvia fruti-cosa EST library
InterPro No. Description UniESTs
sequence
count
IPR016040 NAD(P)-binding 11
IPR012335 Thioredoxin fold 9
IPR005630 Terpene synthase, metal-binding 7
IPR008949 Terpenoid synthase 6
IPR001806 Ras GTPase 6
IPR000719 Protein kinase, core 6
IPR012340 Nucleic acid-binding, OB-fold 5
IPR000886 Endoplasmic reticulum,
targeting sequence
5
IPR005225 Small GTP-binding protein 5
IPR000916 Bet v I allergen 5
IPR012677 Nucleotide-binding, alpha–beta plait 5
IPR013785 Aldolase-type TIM barrel 4
IPR001199 Cytochrome b5 4
IPR001023 Heat shock protein Hsp70 4
IPR001128 Cytochrome P450 4
In the list are presented the families with more than 4 UniEST
members
Table 4 The 25 most represented KEGG pathways
KEGG pathway UniESTs
sequence
count
Enzymes
Oxidative phosphorylation 19 6
Carbon fixation 17 11
Glycolysis/gluconeogenesis 16 9
Biosynthesis of steroids 13 9
Beta-Alanine metabolism 12 6
Urea cycle and metabolism
of amino groups
12 6
Methionine metabolism 11 6
Nucleotide sugars metabolism 10 6
Ubiquitin mediated proteolysis 10 2
Purine metabolism 9 4
Alanine and aspartate metabolism 9 6
Fructose and mannose metabolism 9 4
Glutathione metabolism 8 6
Calcium signaling pathway 8 2
Pantothenate and CoA biosynthesis 8 2
Inositol metabolism 8 4
Citrate cycle (TCA cycle) 8 6
Propanoate metabolism 8 8
Selenoamino acid metabolism 8 4
Terpenoid biosynthesis 8 4
Phenylalanine metabolism 7 3
Pentose phosphate pathway 7 5
Thiamine metabolism 7 2
Pyrimidine metabolism 7 3
Reductive carboxylate cycle (CO2 fixation) 7 5
Metabolic pathway with more than 7 UniESTs are presented
530 Plant Cell Rep (2010) 29:523–534
123
tissues used for the library preparation were harvested in
March at the first strong onset of essential oil production,
whereas the tissues used for the real-time PCR analysis
were harvested in mid-June which is the peak production
period for essential oils. As such, the expression levels of
SfCinS1, SfCinS2 and SfBPPS were probably overrepre-
sented in the June tissues. It should also be noted that the
SfCinS2 has not yet been identified from the other well
studied related Salvia species S. officinalis. Its contribution
to cineole production although less than enzyme 1, is
expected to be significant, as it possesses equivalent cata-
lytic activity by in vitro assays (S. Kampranis, personal
communication). Taken together our results indicate that
the S. fruticosa glandular trichome library is highly rich in
tissue-specific transcripts and complex enough to contain
a series of novel genes associated with secondary
Table 5 The six KEGG pathways related to biosynthesis of secondary metabolites
Biosynthesis of secondary metabolites
EC Name of enzyme UniESTs
KEGG pathway: terpenoid biosynthesis
2.5.1.1 Dimethylallyltranstransferase Contig 40, Contig 88, Salviafruticosa_01_H10_T7
2.5.1.29 Farnesyltranstransferase Contig 88
5.3.3.2 Isopentenyl-diphosphate delta-isomerase Salviafruticosa_05_B01_T7
KEGG pathway: monoterpenoid biosynthesis
4.2.3.11 Sabinene-hydrate synthase Salviafruticosa_06_L11_T7
5.5.1.8 Bornyl diphosphate synthase Contig 92, Salviafruticosa_06_L11_T7
KEGG pathway: phenylpropanoid biosynthesis
2.1.1.68 Caffeate O-methyltransferase Contig 180, Salviafruticosa_04_E11_T7
1.11.1.7 Peroxidase Contig 55, Salviafruticosa_02_J23_T7,
Salviafruticosa_05_M23_T7
1.1.1.195 Cinnamyl-alcohol dehydrogenase Salviafruticosa_04_O24_T7
KEGG pathway: flavonoid biosynthesis
2.1.1.68 Caffeate O-methyltransferase Contig 180, Salviafruticosa_04_E11_T7
KEGG pathway: alkaloid biosynthesis I
1.3.3.8 Tetrahydroberberine oxidase Contig 105
2.6.1.1 Aspartate transaminase Salviafruticosa_04_N15_T7
KEGG pathway: alkaloid biosynthesis II
3.1.1.1 Carboxylesterase Contig 35, Salviafruticosa_03_H03_T7,
Salviafruticosa_03_M01_T7,
Salviafruticosa_04_E03_T7,
Salviafruticosa_04_J22_T7
The enzyme names, the EC numbers and the UniESTs in each pathway are given
Fig. 3 Expression of SfGAPDH
(GenBank: FE536708), SfTPI
(GenBank: FE536366) and
SfIFR (GenBank:GU479926)
transcripts in new and old
leaves. The values are the
mean ± SD of at least three
independent experiments
relative to the fold change of the
transcripts in new leaves
Plant Cell Rep (2010) 29:523–534 531
123
metabolism. Further analysis should enable us to identify
additional minor EST that contributes to natural product
biosynthesis in S. fruticosa.
Acknowledgments We thank M. Georgiadou for technical assis-
tance and N. Dudareva for fruitful colaboration. This work is part of
the 875-03ED research project implemented within the framework of
the ‘‘Reinforcement Programme of Human Research Manpower’’
(PENED) and co-financed by National and Community Funds (25%
from the Greek Ministry of Development-General Secretariat of
Research and Technology and 75% from E.U.-European Social Fund)
and EU-FP7-227448 TERPMED.
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