Complementary DNA library construction and expressed sequence tag analysis of an Arctic moss, Aulacomnium turgidum

Inha University Department of Biological Engineering Incheon 402-751 Republic of Korea
Polar Biology (Impact Factor: 1.59). 05/2009; 33(5):617-626. DOI: 10.1007/s00300-009-0737-8


Unique physiological and metabolic properties of Arctic mosses are responsible for their acclimation to the inclement polar
environment. To perform transcriptome analysis of an Arctic moss species adapted to polar conditions, we constructed a complementary
DNA (cDNA) library using total high-quality RNA extracted from the moss species Aulacomnium turgidum. The library consisted of 1.81×106 of independent clones with 97.41% of recombinants. A total of 509 cDNA clones were sequenced. After eliminating poor quality
sequences, vector trimming and clustering, 360 unigenes consisting of 33 contigs and 327 singletons were identified. Basic
Local Alignment Search Tool X searches generated 245 significant hits (E value <10−5). For further Gene Ontology analysis, 158 unigenes were annotated and classified with terms for molecular function, biological
process and cellular component. Among the expressed sequence tags, seven genes were selected based on their putative roles
in stress response, and they showed enhanced transcripts level under various abiotic stresses such as low temperature, heat
and high-salinity. Also, two rare-cold-inducible genes showed different expression patterns under low temperature and UV-B
treatment, indicating their distinct roles in adaptation to Arctic environment. Although experiments have been conducted on
a limited scale, this study provides useful information for better understanding the mechanism of stress acclimation of polar
mosses and material basis for potential genomic modification for higher plants to increase stress tolerance.

KeywordsArctic moss-
Aulacomnium turgidum
-Expressed sequence tags (ESTs)-Gene Ontology (GO)


Available from: Hyoungseok Lee, May 16, 2014
Polar Biol (2010) 33:617–626
DOI 10.1007/s00300-009-0737-8
Complementary DNA library construction and expressed
sequence tag analysis of an Arctic moss, Aulacomnium turgidum
Shenghao Liu · Hyoungseok Lee · Pil-Sung Kang ·
Xiaohang Huang · Joung Han Yim · Hong Kum Lee ·
Il-Chan Kim
Received: 7 January 2009 / Revised: 24 September 2009 / Accepted: 25 September 2009 / Published online: 21 October 2009
© Springer-Verlag 2009
Abstract Unique physiological and metabolic properties
of Arctic mosses are responsible for their acclimation to the
inclement polar environment. To perform transcriptome
analysis of an Arctic moss species adapted to polar condi-
tions, we constructed a complementary DNA (cDNA)
library using total high-quality RNA extracted from the
moss species Aulacomnium turgidum. The library consisted
of 1.81 £ 10
of independent clones with 97.41% of recom-
binants. A total of 509 cDNA clones were sequenced. After
eliminating poor quality sequences, vector trimming and
clustering, 360 unigenes consisting of 33 contigs and 327
singletons were identiWed. Basic Local Alignment Search
Tool X searches generated 245 signiWcant hits (E value
). For further Gene Ontology analysis, 158 unigenes
were annotated and classiWed with terms for molecular
function, biological process and cellular component.
Among the expressed sequence tags, seven genes were
selected based on their putative roles in stress response, and
they showed enhanced transcripts level under various abi-
otic stresses such as low temperature, heat and high-salinity.
Also, two rare-cold-inducible genes showed diVerent
expression patterns under low temperature and UV-B treat-
ment, indicating their distinct roles in adaptation to Arctic
environment. Although experiments have been conducted
on a limited scale, this study provides useful information
for better understanding the mechanism of stress acclima-
tion of polar mosses and material basis for potential geno-
mic modiWcation for higher plants to increase stress
Keywords Arctic moss · Aulacomnium turgidum ·
Expressed sequence tags (ESTs) · Gene Ontology (GO)
The Arctic constitutes a unique and important environment
with a signiWcant role in the dynamics and evolution of the
earth system (Birks et al. 2004). In the Arctic, plants are
exposed to extreme amplitudes of environmental factors:
early snow and frost, drought, wind abrasion and extreme
temperatures on open patches (Billings and Mooney 1968).
They developed a variety of strategies that range from
physiological adaptations to tolerance to stressful environ-
mental factors. Examples of adaptive mechanisms to low
temperature include the evolution of cold shock and anti-
freeze proteins, the modulation of the kinetics of key
enzymes, and the development of more Xuid biological
membranes through the accumulation of polyunsaturated
fatty acyl chains (Morgan-Kiss et al. 2006).
Mosses are one of the most diverse and widespread
groups of plants and often form the dominant vegetation in
many Arctic tundra plant communities (Longton 1997;
Ayres et al. 2006; Gornall et al. 2007). In contrast to a wide
range of taxa already analyzed in the Antarctic (Skotnicki
et al. 2000, 2005), few studies so far focused on the genetic
diversity of Sphagnum species in the Arctic (Flatberg and
S. Liu · H. Lee · P.-S. Kang · J. H. Yim · H. K. Lee · I.-C. Kim (&)
Polar BioCenter, Korea Polar Research Institute (KOPRI),
KORDI, Incheon 406-840, Republic of Korea
S. Liu · X. Huang
Key Laboratory of Marine Bioactive Substances,
The First Institute of Oceanography,
State Oceanic Administration, 266061 Qingdao, China
P.-S. Kang
Department of Biological Engineering, Inha University,
Incheon 402-751, Republic of Korea
Page 1
618 Polar Biol (2010) 33:617–626
Thingsgaard 2003; Greilhuber et al. 2003). Mosses repre-
sent one of the oldest clades of land plants, separated by
approximately 450 million years of evolution from crop
plants. Consequently, mosses contain metabolites and
genes not known from these seed plants (Reski and Frank
2005). Therefore, Arctic mosses may oVer exceptional
opportunities for gaining novel insights into the mecha-
nisms of plant survival under extreme conditions and plant
genetic evolution.
Large-scale random sequencing of expressed sequence
tags (ESTs) provides an eVective means of identifying
expressed genes in organisms across all kingdoms. In
plants, for example, a number of genes from rice have been
reported to be induced by drought, high-salinity, and low-
temperature stresses, and their products are thought to func-
tion in stress tolerance and adversity response (Rabbani
et al. 2003). To date, over 300,000 ESTs from the model
species Physcomitrella patens have been deposited in
GenBank (
summary.html). However, to our knowledge, there is no
report on identifying the stress-related genes from a comple-
mentary DNA (cDNA) library of polar mosses. In the present
study, we constructed a cDNA library and then conducted an
EST analysis for an Arctic moss, Aulacomnium turgidum. In
addition, we identiWed several stress-related genes using
annotation searches from the dataset.
Materials and methods
Plant materials and stress treatments
Aulacomnium turgidum specimens growing under natural
conditions were collected in the vicinity of the Korean
Dasan Arctic Station (78°54N; 11°57W) near Ny-Ålesund,
Svalbard, in August 2006. They were placed in plastic
containers and transported to Korea, where they were then
cultivated on BCD solid media (Ashton and Cove 1977) in
a growth room at 25°C with continuous light. For the cold
or the heat treatments, plants were transferred from 25 to 4
or 37°C and incubated for 24 h. For the salt treatment,
plants were transferred to BCD solid media containing
300 mM NaCl and incubated at 25°C for 24 h. UV-B treat-
ments were performed in a dark box at a constant 15°C.
UV-B irradiation was supplied by two Philips UV-B lamps
(TL 20 W/01 RS). Photon Xuxes were adjusted to 9 W/m
by varying the distance of the leaves from the light source.
Fluence was measured using an digital ultraviolet radiome-
ter model SM 6.0 UVB (Solartech Inc., USA). Some green
parts of shoots and protonemata were ground in liquid
nitrogen with mortar and pestle and then the ground powder
was transferred into 50 mL conical tubes and stored at
Total and poly A
RNA preparation
Total RNA was extracted from 3 to 4 g of ground tissue
using cetyltrimethylammonium bromide (CTAB) extrac-
tion buVer (Fu et al. 2004) composed of 2% CTAB, 1%
polyvinylpyrrolidone (PVP) K-30 (soluble), 100 mM Tris
HCl (pH 8.0), 20 mM EDTA, 1.4 M NaCl, 0.5 g/L spermi-
dine (free acid), 2% -mercaptoethanol (added just before
use). Solutions were treated with diethylpyrocarbonate and
autoclaved (Sambrook et al. 1989). Tris–HCl (pH 8.0), pre-
pared with DEPC-treated water, was added to the appropri-
ate solutions post-autoclaving.
After adding 0.5 mL CTAB buVer (2% -ME) to 0.5 mL
powder, the samples were incubated at 60°C for 10 min,
mixed well by vortexing. The samples were further
extracted twice with an equal volume of chloroform:iso-
amyl alcohol (24:1) centrifuged at 13,000 rpm for 10 min at
4°C and the aqueous phase was transferred to a new tube.
To ensure obtaining a high-quality RNA, the interphase
was carefully avoided being transferred. The gained super-
natant was precipitated with 1/4 volume of 10.0 M LiCl to
each tube and mixed well by inverting. The RNA was pre-
cipitated overnight at 4°C and harvested by centrifugation
at 13,000 rpm for 30 min at 4°C. Pellet was washed with
75% ethanol twice and air-dried for 5 min. RNA was dis-
solved in 100 L DEPC-treated water and RNA from the
same samples were pooled together into new 1.5-mL
RNAse-free microfuge tubes.
Poly A
RNA was isolated using an Oligotex Mini Kit
(Qiagen, Los Angeles, CA). The puriWed total RNA and
poly A
RNA were quantiWed with a ND-1000 spectropho-
tometer (NanoDrop Technologies Inc.) at wavelengths of
230, 260 and 280 nm. The integrity of total RNA and poly
RNA was veriWed by running samples on 1.2% denatur-
ing agarose gels.
Construction of cDNA library
First-strand cDNA was synthesized from approximately
500 ng of total RNA using the SMART cDNA Library
Construction Kit (DB Clontech, USA) according to the
manufacturer’s protocol. Double stranded cDNA was syn-
thesized by employing long-distance PCR (LD-PCR) from
2 L of poly A
RNA. After size fractioning, cDNA was
cloned into the bacteriophage expression vector TriplEx2
and packaged into phage particles using ZAP-cDNA Giga-
pack III Gold Cloning Kit (Stratagene, USA) to construct
the primary cDNA library. Phages were used to transfect
XL1-Blue to amplify the primary cDNA library.
Positive clones were checked by PCR with TriplEx
LD-insert screening primers. To increase the stability of
cDNA library, primary library was ampliWed as described
in the manufacturer’s instructions.
Page 2
Polar Biol (2010) 33:617–626 619
Sequence processing
Clones for sequencing were selected randomly from the
cDNA library. Each clone was cultured and the plasmid
DNA was extracted with an AccuPrep Plasmid Extraction
Kit (Bioneer, Korea). The sequencing reaction with
pTriplEx2 5 sequencing primer was performed on an ABI
PRISM 3100 Genetic Analyzer (Applied Biosystems,
Raw sequences were Wrst individually processed using
Phred software (CodonCode Aligner) which linked base
calling, eliminating sequences shorter than 100 bp, low-
quality sequences and vector trimming. The overlapping
sequences (from both 3 and 5 ends) were evaluated and
aligned into full consensus sequence contigs using DNA
analyzing software Lasergene 7.0 (DNAStar, Madison, WI,
USA). The non-overlapping sequences were formatted and
treated as singlet sequences.
Gene Ontology (GO) assignments
For functional classiWcation according to GO assignments,
all unigene sequences were queried against the National
Center for Biotechnology Information (NCBI) non-redun-
dant (nr) protein database using BLASTX algorithm with
the E value threshold set to ·10
. Functional categories
were deWned using Gene Ontology Database (http:// and BLAST algorithm with
default settings. According to BLAST results, the top 158
BLAST hits were selected for further analysis. Gene sym-
bols associated with the best scoring BLAST hits were
assigned back to the original query nucleotide sequence and
later used in GO Slimmer search. All searched gene sym-
bols were uploaded to the Slimmer tool of AmiGO software
for mapping the granular annotations using plant GO slim
(Suparna Mundodi, December 2002). Based on these GO
term assignments, the complete unigene EST set for the
cDNA library was organized around GO hierarchies and
divided into three categories: biological processes, cellular
components and molecular functions (Harris et al. 2004).
Quantitative, real-time RT-PCR
Quantitative real-time PCR (qRT-PCR) was performed to
analyze the expression of selected genes from both samples
using gene-speciWc PCR primers. Total RNA (2 g) was
used as template for reverse transcription with the MMLV
Reverse Transcriptase (EnZynomics, Korea). qRT-PCR
was conducted using the SYBR Green PCR Kit (TaKaRa)
in a total volume of 10 L on an Rotor-Gene 6000 PCR
machine (Corbett, Australia). A melting curve was
recorded at the end of every run to assess product speciWc-
ity. For each target gene, PCR conditions (primer concen-
trations and cDNA quantity) were optimized and PCR
eYciency was determined. Experimental samples were
evaluated in triplicate and qRT-PCR reactions for each
were run in duplicate. Target gene expression was normal-
ized with actin and corrected according to the PCR
eYciency value. The products of qRT-PCR were run on
agarose gels and consistently showed accurate molecular
RNA isolation and cDNA library construction
High-quality total RNA was obtained using modiWed
CTAB extraction buVer. The formaldehyde agarose gel
electrophoresis demonstrated that the extraction protocol
described here was eYcient in yielding a high quality of
total RNA from all moss tissues and control grass species
(Deschampsia antarctica; Fig. 1a). The yields of total RNA
(g/g fresh weight) were as follows: 20–30 for brown tissue
of mosses, 80–126 for green tissue of mosses and 364–415
for grass.
For all samples, the A260/230 ratio was higher than 2.0.
This indicated that the RNA was of high purity and without
polyphenol and polysaccharide contamination. The A260/
280 ratios ranged from 1.91 to 2.02, indicating lack of pro-
tein contamination. The RNA integrity was assessed by the
sharpness of ribosomal RNA bands visualized on a denatur-
ing 1.2% agarose gel. For all RNA samples tested, two
Fig. 1 a Total RNA isolated using the CTAB extraction protocol was
separated on a 1.2% denaturing formaldehyde agarose gel and stained
with ethidium bromide. M 1 kb DNA ladder, 1 control grass total RNA
(»4 g), 2 moss total RNA (»1 g), 3 moss total RNA (»0.5 g).
b Agarose gel electrophoresis of Poly A
RNA extracted from total
RNA of Arctic moss. M 1 kb DNA ladder, 1 poly A
RNA. c Agarose
gel electrophoresis of double stranded cDNA ampliWed by long-
distance PCR. M 1 kb DNA ladder, 1 double stranded cDNA
Page 3
620 Polar Biol (2010) 33:617–626
distinct bands (28S and 18S ribosomal RNA) at approxi-
mately 4.5 and 1.9 kb without degradation were observed,
respectively (Fig. 1a).
Poly A
RNA was isolated using oligo d(T) cellulose
column. Gel electrophoresis showed that moss poly A
was enough for high-quality cDNA library construction
(Fig. 1b). Double-strand cDNA was generated by LD-PCR
and showed a large size distribution (0.1–10 kb) by electro-
phoresis gel analysis (Fig. 1c).
After construction of cDNA library, the titer was deter-
mined using phages to transfect XL1-Blue. The result showed
that the titer was 3.62 £10
pfu/mL and the library consisted
of 1.81 £ 10
recombinants, the recombinant rate was
97.41%. For better preservation, the cDNA library was ampli-
Wed, resulting at least 9.83 £10
pfu/mL. Ten monoclonal
recombinant phages were picked up randomly and PCR was
performed to verify the size of cDNA inserts in the phages.
The PCR products were electrophoresed on 1.2% agarose gel
and their sizes were ranged from 0.5 to 2.0 kb (Fig. 2).
Fig. 2 cDNA inserts were veriWed by PCR and visualized on 1.2%
agarose gel electrophoresis. M 1 kb DNA ladder, 110 PCR products
Table 1 Representative genes in the A. turgidum cDNA library
ID ESTs Representative
E value Length Description
Contig02 8 MC28 8.00E¡58 1,128 Cytochrome b559 subunit alpha [Spinacia oleracea]
Contig03 2 MD13 7.00E¡06 1,334 Predicted protein [Physcomitrella patens subsp. patens]
Contig04 4 MC94 1.00E¡24 1,048 Conserved hypothetical protein [Magnetospirillum gryphiswaldense]
Contig05 2 MB47 9.00E¡40 1,025 Eukaryotic release factor 3 [Ricinus communis]
Contig06 2 MG85 6.00E¡145 1,193 Polyubiquitin [Pinus sylvestris]
Contig07 3 MC78 1.00E¡106 1,482 Predicted protein [Physcomitrella patens]
Contig08 2 MC39 2.00E¡18 1,010 Choline kinase [Pisum sativum]
Contig09 2 MI31 9.00E¡61 706 Heat-shock protein 60 [Ageratina adenophora]
Contig11 3 MG72 4.00E¡59 950 Predicted protein [Physcomitrella patens]
Contig13 3 MA66 3.00E¡22 711 Enhanced disease susceptibility 5 [Arabidopsis thaliana]
Contig14 3 MC60 2.00E¡12 700 Low temperature-induced protein [Hordeum vulgare subsp. vulgare]
Contig15 2 MA84 3.00E¡33 701 Probable thioredoxin H [Picea mariana]
Contig17 2 MF90 4.00E¡59 975 Ribosomal protein S12 [Physcomitrella patens]
Contig19 2 ML45 6.00E¡87 1,245 Predicted protein [Physcomitrella patens]
Contig20 2 MI20 9.00E¡11 683 Predicted protein [Physcomitrella patens]
Contig21 2 MF71 7.00E¡43 759 Binding protein [Arabidopsis thaliana]
Contig23 2 MD88 4.00E¡27 929 Predicted protein [Physcomitrella patens]
Contig24 2 MA52 1.20E¡86 863 19s proteasome subunit 9 [Arabidopsis thaliana
Contig25 2 MN47 1.00E¡57 680 Predicted protein [Physcomitrella patens]
Contig27 2 MC14 3.00E¡55 1,249 Alcohol dehydrogenase [Neosartorya Wscheri NRRL]
Contig28 2 MH90 9.00E¡32 1,039 Predicted protein [Physcomitrella patens]
Contig29 2 ML95 9.00E¡32 944 RNA polymerase [Physcomitrella patens]
Contig30 6 MJ89 2.00E¡08 685 Low temperature and salt responsive protein [Sonneratia alba]
Contig31 2 MD82 7.00E¡21 751 GSH-dependent glutathione dehydrogenase [Arabidopsis thaliana]
Contig32 2 MC97 2.00E¡58 874 Phosphoglyceromutase [Malus domestica]
Contig33 2 MH46 7.40E¡80 923 Cholinephosphate cytidylyltransferase [Arabidopsis thaliana]
Page 4
Polar Biol (2010) 33:617–626 621
General characteristics of A. turgidum ESTs
A total of 509 cDNA clones were randomly selected from
the library and single-pass sequences were generated. The
sequences of poor quality and of <100 bases were removed,
and the Wnal EST number was 437 with mean lengths of
617 bp (GenBank Accession No. from FL685677 to
FL686115). Cluster analysis revealed 360 unigenes of 33
contigs and 327 singletons with a redundancy level of
9.2%. The sequences of 360 unigenes were translated into
all possible reading frames, and compared with those in
NCBI non-redundant protein database. Among these
sequences, approximately 46.0 and 22.2%, respectively,
had signiWcant matches with sequences in the non-redundant
protein database (E value ·10
), which encode for
“known proteins” and “predicted/unknown proteins” based
on the BLASTX results. In addition, 31.9% of the ESTs
showed no similarity to any sequences in the database
Percentage representa-
tion of Gene Ontology mappings
for ESTs of the Arctic moss
ulacomnium turgidum
Page 5
622 Polar Biol (2010) 33:617–626
(E value ¸10
) and were deemed “No signiWcant simi-
larity found”. Furthermore, more than 74.5% of the
“predicted/unknown protein” in our libraries matched
Physcomitrella patens EST sequence, annotated as pre-
dicted. After sequence assembly, results showed that the
highest number of sequences clustered into one contig was
8. The representative genes with E value ·10
are shown
in Table 1.
Functional analysis of ESTs
AmiGO software for BLAST searching the Gene Ontology
Database was used under the default setting to determine
similarity to the known genes and extract gene symbols for
grouping sequences into functional classiWcations. In total,
158 annotations acquired with gene symbols were exported
into a Microsoft Excel data sheet and sorted manually. In
Table 2 Stress-related genes isolated from the A. turgidum cDNA library
ID E value Putative identity Related stress incidents
Contig08 3.00E¡19 Choline kinase [Oryza sativa] Salinity stress
MC32 1.40E¡48 DEAD/DEAH box helicase, putative (RH17) [Arabidopsis thaliana] Salinity stress
ML12 4.90E¡72 NADP + isocitrate dehydrogenase [Arabidopsis thaliana] Salinity stress
Contig32 2.40E¡47 Phosphoglycerate mutase [Arabidopsis thaliana] Drought-stress
MC48 4.50E¡23 Oxidoreductase [Arabidopsis thaliana] Drought-stress
Contig09 9.00E¡61 Heat-shock protein 60 [Ageratina adenophora] Thermal and oxidative stresses
MG69 1.00E¡18 2,3-Biphosphoglycerate-independent phosphoglycerate
mutase [Arabidopsis thaliana]
Thermal and oxidative stresses
Contig24 1.20E¡86 19s proteasome subunit 9 [Arabidopsis thaliana] Thermal and oxidative stresses
MG84 3.80E¡67 20S proteasome alpha subunit B1 [Arabidopsis thaliana] Thermal and oxidative stresses
MJ67 1.80E¡85 20S proteasome beta subunit C1 [Arabidopsis thaliana] Thermal and oxidative stresses
MG61 2.70E¡31 26S proteasome regulatory subunit S2 1A [Arabidopsis thaliana] Thermal and oxidative stresses
MC42 7.50E¡32 Ubiquitin-protein ligase [Arabidopsis thaliana] Thermal and oxidative stresses
Contig06 1.70E¡135 Polyubiquitin10 [Arabidopsis thaliana] Thermal and oxidative stresses
MB35 5.40E¡41 Histone mono-ubiquitination 2 [Arabidopsis thaliana] Thermal and oxidative stresses
MK56 3.70E¡30 Ubiquitin-speciWc protease [Arabidopsis thaliana] Thermal and oxidative stresses
MJ85 2.40E¡24 Phospholipase A2 [Arabidopsis thaliana] Thermal and oxidative stresses
Contig15 5.30E¡29 Thioredoxin H-type 9 [Arabidopsis thaliana] Oxidative stress
MG80 3.90E¡19 Thioredoxin (Trx) [Arabidopsis thaliana] Oxidative stress
MF95 5.70E¡23 Aldo–keto reductase family 1, member A1a [Arabidopsis thaliana] Oxidative stress
ML01 8.60E¡14 UDP-glycosyltransferase [Arabidopsis thaliana] Oxidative stress
MN78 1.50E¡33 Peroxidase/catalase [Arabidopsis thaliana] Oxidative stress
Contig02 8.00E¡58 Cytochrome b559 subunit alpha [Spinacia oleracea] Freezing and thawing stresses
or solar radiation
Contig14 9.10E¡16 Rare-cold-inducible 2a [Arabidopsis thaliana] Cold and freezing stresses
Contig30 9.40E¡10 Rare-cold-inducible 2b [Arabidopsis thaliana] Cold-response or freezing tolerance
MD71 2.80E¡22 Regulator of chromosome condensation [Arabidopsis thaliana] Cold tolerance
MG53 1.60E¡10 Alcohol dehydrogenase [Arabidopsis thaliana] Low temperature
MA16 2.70E¡09 Ankyrin repeat-containing protein [Schizosaccharomyces pombe] Disease resistance and
antioxidation metabolism
ME79 3.40E¡61 1,3-Beta-glucan synthase [Arabidopsis thaliana] Wounding, physiological stress,
MJ19 4.30E¡32 Copper amine oxidase, putative [Arabidopsis thaliana] Signal in abscisic acid (ABA)
MC67 1.00E¡64 Protein phosphatase 2C family protein [Arabidopsis thaliana] Hormone abscisic acid (ABA) signaling
Contig27 2.50E¡45 Glutathione-dependent formaldehyde dehydrogenase
[Schizosaccharomyces pombe]
Wounding, jasmonic acid
and salicylic acid
Contig13 3.90E¡21 Enhanced disease susceptibility 5 [Arabidopsis thaliana] DetoxiWcation
MJ02 4.20E¡105 Pyruvate dehydrogenase kinase [Arabidopsis thaliana] Abiotic stress
MA98 1.80E¡38 Trehalose-6-phosphate synthase [Arabidopsis thaliana] Stress tolerance/cell shape
and plant architecture
MH85 2.10E¡103 Long-chain fatty-acid–CoA ligase [Arabidopsis thaliana] Tolerance to biotic and abiotic stresses
Page 6
Polar Biol (2010) 33:617–626 623
this way more than 93% of the matches came from the Ara-
bidopsis thaliana genome, whereas only 11 matches were
found in Nicotiana sylvestris, Nostoc sp. PCC 7120,
Schizosaccharomyces pombe and Dictyostelium discoid-
A more detailed functional annotation was performed by
mapping assigned unique gene symbols to the Gene Ontol-
ogy Consortium structure which provides a structured and
controlled vocabulary to describe gene products according
to three ontologies: cellular components, biological pro-
cesses and molecular functions. The most represented
biological processes were “cellular” and “metabolic”,
accounting for 28.8 and 23.2%, respectively, of the total
158 unique sequences assigned with at least one GO term
(Fig. 3a). In terms of cellular components, 43.7% were
related to “cytoplasm” (Fig. 3b). In terms of molecular
functions, 44% were involved in “catalytic activity” and
42.4% in “binding activity” (Fig. 3c).
In addition, 35 unigenes showing similarity to proteins
related to stress incident were presented in Table 2. Among
them, 17, 5, 3 and 2 genes are candidates for oxidative
stress, cold stress, salinity stress and abscisic acid (ABA)-
inducible genes, respectively. To conWrm the relationship
of those genes and various stress responses, we performed
quantitative RT-PCR analyses with gene-speciWc primer
sets (Table 3). Seven genes from Table 2 were analyzed,
and actin was used as a quantitative control. The results of
the RT-PCR analysis agreed in most cases with expecta-
tions from GO analysis.
As two genes showing signiWcant similarity with RCI2a
(rare-cold-inducible 2a) and RCI2b from Arabidopsis
showed four- and tenfold mRNA accumulation by low
temperature (Fig. 4a), they were selected to investigate the
relationship between speciWc gene expression and Arctic
environmental conditions, cold and UV-B irradiation.
AtuRCI2a and AtuRCI2b from A. turgidum are 54 and 59
amino acids, respectively. Their sequence alignment
revealed 65% identity and 84% similarity between them
(Fig. 5a). Their counterparts from other plant species
showed overall similarity, which suggests that these pro-
teins are conserved throughout the plant kingdom. Hydrop-
athy analyses indicated that they are highly hydrophobic
and contain two potential transmembrane domains (data
not shown). Under cold treatment, both AtuRCI2a and
AtuRCI2b mRNAs accumulated gradually, reaching the
peak after 1 and 2 days, respectively (Fig. 5B). AtuRCI2b
transcripts have shown more rapid and high expression
level than AtuRCI2a. However, under UV-B treatment,
AtuRCI2a mRNA accumulated upto 10 times the basal
level and AtuRCI2a mRNA was not induced (Fig. 5c).
Isolating high-quality nucleic acid is a prerequisite for
molecular biological studies. However, isolating high-qual-
ity RNA from Arctic mosses is quite diYcult because of
their richness in polyphenols, polysaccharides and second-
ary metabolites. In the present study, we employed a CTAB
extraction method with 1.4 M NaCl and 1% PVP, suitable
for isolating high-quality RNA from moss tissues. LiCl is
used to precipitate RNA rather than alcohol with a monova-
lent cation, because LiCl will not eYciently precipitate
DNA, protein or carbohydrate (Birnboim 1992). Finally,
the yield of total RNA was 80–126 g/g for green tissue of
mosses and the quality was conWrmed to be superior by
spectrophotometer and formaldehyde agarose gel (Fig. 1).
A cDNA library should represent all expressed genes in
the tissue from which the library was constructed. In this
research, SMART technique was used to construct a cDNA
library of A. turgidum tissues, resulting in at least
1.81 £ 10
recombinants in the primary library. ESTs with
the mean lengths of 617 bp also showed that the sequence
integrality of recombinant cDNA was good in quality.
BLAST was used to search the entire NCBI GenBank with
an E value threshold of 10
, which revealed 46% of the
Table 3 Primer pairs used in
the qRT-PCR analysis
Target Forward Reverse
Sequence (5 ! 3)
Page 7
624 Polar Biol (2010) 33:617–626
cDNA clones with high homologies to genes with known
functions in the database. The results showed that the most
representative genes in our library are cytochrome b559
subunit alpha, low temperature and salt responsive protein,
polyubiquitin and enhanced disease susceptibility 5
(Table 1). In a previous study of ESTs of Deschampsia ant-
arctica, an Antarctic extremophile angiosperm plant
species, photosynthesis-related genes were most abundant
(Lee et al. 2008). In A. turgidum, the portion of stress-
related genes is relatively high, which might be caused to
some extent by the cDNA ampliWcation step during cDNA
library preparation.
Automatic functional annotation methods basically rely
on the sequence, structure, phylogenetic or co-expression
relationships between known and novel sequences (Frishman
2007). Most tools provide GO annotation of sequences data
through homology searches. However, function transfer
from homologous sequences is comparatively highly error
prone (Jones et al. 2007). In our study, we explored BLAST
Search of the GO website and assigned functional symbols
manually. Manual curation guarantees a high level of anno-
tation correctness. Finally, the oYcial software AmiGO
was used for the high-throughput functional annotation
according to GO hierarchies. A relatively high number of
stress-related genes were isolated from cDNA library and
annotated in the dataset (Table 2).
A group of proteins, part of the plant antioxidant system,
are rapidly activated in response to oxidative stress gener-
ated by heat, including superoxide dismutases, catalases
and peroxidases. Modulation of the heat stress response is
also dependent on cellular control of degradation and main-
tenance of quality of proteomes by the ubiquitin–protea-
some system (Mathew and Morimoto 1998; Mathew et al.
1998). Therefore, we identiWed a total of 17 genes related to
oxidative stress, which was more than the genes related to
cold stress, salinity stress or ABA-induction (Table 2).
Heat-shock proteins (Hsps)/chaperones are responsible
for protein folding, assembly, translocation and degradation
in many normal cellular processes, stabilize proteins and
membranes, and can assist in protein refolding under stress
conditions (Wang et al. 2004). The HSP60 in chloroplasts
is the Rubisco subunits binding protein also known as chlo-
roplast chaperonin (Yordanov 1995). In present study, we
identiWed a HSP60 gene which assembled from two ESTs
of moss cDNA library and its expression was induced by
the heat and also by the cold (Fig. 4). Therefore, the com-
mon action of HSPs in Arctic moss may involve in mitiga-
tion of temperature changing, protecting proteins against
oxidation damage and folding of newly synthesized pro-
To endure freezing and thawing stress in Arctic, mosses
could also reduce the eYciency of photosystem II (PSII)
which protect them from photoinhibitory damage in envi-
ronments where freezing temperatures occur in conjunction
with high levels of solar radiation (Lovelock et al. 1995).
Using isolated reaction centers of PSII, Barber and De Las
Rivas (1993) conWrmed that the low potential form of cyto-
chrome b559 can accept electrons directly from reduced
pheophytin and protect the reaction center against photoin-
hibition. In this study, cytochrome b559 constitutes the
most abundantly expressed gene in A. turgidum, indicating
Fig. 4 Quantitative RT-PCR analysis of various stress-related genes
from A. turgidum under abiotic stresses treatments. Fold changes were
calculated by comparing gene expression in plants under stress condi-
tions with control plants without stress treatment after normalization
with the actin gene of A. turgidum. Cold, incubation at 4°C for 24 h (a);
heat, incubation 37°C for 24 h (b); NaCl, incubation with 300 mM
NaCl for 24 h (c)
Page 8
Polar Biol (2010) 33:617–626 625
a photosynthetic acclimation to low levels of temperature
and solar radiation.
Glutathione dehydrogenase, glutathione-dependent
formaldehyde dehydrogenase and enhanced disease suscep-
tibility 5 are related to plant antioxidation, detoxiWcation
and pathogen resistance, respectively (Achkor et al. 2003;
Rogers and Ausubel 1997). Other genes identiWed from
cDNA library and EST analysis may implement their possi-
ble roles in plant survival in harsh polar condition.
From A. turgidum cDNA library, two new rare-cold-
inducible (RCI) genes were isolated. They encode very
small (50–60 residues) and highly hydrophobic proteins
with two potential transmembrane domains, constituting
small gene families in various plant species (Goddard et al.
1993; Capel et al. 1997; Brown et al. 2001). They are con-
sidered to be localized in the plasma membrane, which is
the primary target of stress recognition, suggesting their
signiWcance in a broad range of stress conditions such as
low temperature, freezing, and high-salinity. In this study,
two RCI genes were cloned from A. turgidum. While their
expression patterns were similar in the cold treatment, these
diVered clearly more in the UV-B treatment, suggesting
that they play divergent roles under diVerent abiotic stress
conditions in the Arctic (Fig. 5b, c). Further studies will
focus on identifying the activation mechanisms of these
genes under various abiotic stresses, as shown for Arabid-
opsis RCI proteins (Medina et al. 2001). As far as we know,
this is the Wrst report on RCI gene expression under UV-B
Here, we have presented and discussed only an initial
analysis of the EST dataset and further characterized
selected examples with emphasis on genes with putative
roles in stress response. The amount of redundancy present
in the EST dataset is relatively low. However, identiWcation
of novel genes, determination of their expression patterns,
and an improved understanding of their functions in stress
adaptation gained through this study will provide us the
basis of eVective engineering strategies to improve stress
Acknowledgments The research was Wnancially supported by a
Grant PE08050 from the Korea Polar Research Institute.
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  • Source
    • "Total RNA was extracted from liquid nitrogen ground algae powder using cetyl trimethylammonium bromide (CTAB) extraction buffer composed of 2% CTAB, 1% polyvinylpyrrolidone K-30 (soluble), 100 mM Tris–HCl (pH 8.0), 20 mM EDTA, 1.4 M NaCl, 0.5 g/L spermidine (free acid), 2% β-mercaptoethanol (added just before use; Liu et al. 2010). After adding 0.5 mL CTAB buffer (2% β-ME) to the ground powder, the samples were incubated at 60°C for 10 min and mixed well by vortexing. "
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