RESEARCH ARTICLE

Developmental stage-dependent differential gene expressionof superoxide dismutase isoenzymes and their localizationand physical interaction network in rice (Oryza sativa L.)

Krishna Nath • Susheel Kumar • Roshan Sharma Poudyal • Young Nam Yang •

Rupak Timilsina • Yu Shin Park • Jayamati Nath • Puneet Singh Chauhan •

Bijaya Pant • Choon-Hwan Lee

Received: 17 April 2013 / Accepted: 22 August 2013

� The Genetics Society of Korea 2013

Abstract Superoxide dismutase (SOD) isoenzymes are

essential for scavenging excess reactive oxygen species in

living organisms. So far, expression pattern of SOD iso-

enzymes genes along leaf development plus their sub-cel-

lular localization and physical interaction network have not

yet been clearly elucidated. Using multiple bioinformatics

tools, we predicted the sub-cellular localizations of SOD

isoforms and described their physical interactions in rice.

Using in silico approaches, we obtained several evidences

for existence of seven SOD genes and a SOD copper

chaperone gene. Their transcripts were differentially

expressed along with different developmental stage of rice

leaf. Finally, we performed quantitative real time-poly-

merase chain reaction (qRT-PCR) to validate in silico

differential expression pattern of SOD genes experimen-

tally. Expression of two cytosolic cCuZn-SODs was high

during the whole vegetative stage. Two plastidic Fe-SODs

were found and their expression levels were very low and

started to increase from the late vegetative stage. Their

expression patterns were very similar to each other, indi-

cating the formation of heterodimer. However, their

expression patterns are different from those for Arabidopsis

Fe-SODs. The expression of pCuZn-SOD was very high in

the early developmental stage, but qRT-PCR results were

different, which remains for further study. From the results

on the differential expression of SOD genes, we can

understand the role of each SOD gene and even predict

their role under certain circumstances based on in silico

analysis.

Keywords Antioxidant isoenzymes �Computational bioinformatics analysis � Differential

gene expression � Reactive oxygen species �Sub-cellular localization � Superoxide dismutase

Introduction

Reactive oxygen species (ROS) are produced in the chlo-

roplasts, mitochondria, and peroxisomes as byproducts of

several essential aerobic reactions during metabolic pro-

cesses (Karuppanapandian et al. 2011). Accumulation of

these ROS under environmental stresses affects cellular

functions by damaging nucleic acid and oxidizing proteins,

thus leading to a loss in crop productivity (Mittler 2002;

Apel and Hirt 2004; Foyer and Noctor 2005). Therefore, to

balance or minimize these lethal effects, phototropic

organisms employ an array of ROS-scavenging systems

that involve superoxide dismutase (SOD), ascorbate

Krishna Nath and Susheel Kumar have equally contributed to this

work.

K. Nath (&) � R. Timilsina

Department of New Biology, DGIST, Daegu 711-873,

Republic of Korea

e-mail: krishnanath@gmail.com

K. Nath � R. S. Poudyal � Y. N. Yang � J. Nath � C.-H. Lee (&)

Department of Molecular Biology, Pusan National University,

Pusan 609-735, Republic of Korea

e-mail: chlee@pusan.ac.kr

S. Kumar � P. S. Chauhan

Center for Plant Molecular Biology, CSIR-National Botanical

Research Institute, Lucknow 226001, India

Y. S. Park

Center for Core Research Facilities, DGIST, Daegu 711-873,

Republic of Korea

B. Pant

Central Department of Botany, Tribhuvan University,

Kathmandu, Nepal

123

Genes Genom

DOI 10.1007/s13258-013-0138-9

peroxidase, catalase, peroxidase, and glutathione S-trans-

ferase (Asada and Takahashi 1987; Bowler et al. 1991;

Bowler and van Montagu 1992; Mittler 2002; Gill and

Tuteja 2010).

Of all isoenzymes, SODs constitute the first line of

defense against toxic superoxide radicals, rapidly con-

verting superoxide into H2O2 and molecular oxygen

(Fridovich 1995). Six SODs have been reported in higher

plants, classified into three groups according to their metal

cofactor: copper zinc (CuZn-SOD), manganese (Mn-SOD),

and iron (Fe-SOD). These isoforms show differential sen-

sitivities to dismutation of superoxide into H2O2 and

molecular oxygen (Bowler and van Montagu 1992; Bowler

et al. 1994), as well as in the catalytically active metal they

require and their sub-cellular localization (Abreu and Ca-

belli 2010). At the molecular level, SOD genes are also

differentially expressed in plants in response to oxidative

stresses.

Although the roles of SODs have been attributed to

various vital processes like growth and development, pro-

gram cell death, stress responses and systematic signaling,

their subcellular localization, and physical interaction

partners have not yet been elucidated in plant species. In

this study, we have done several comprehensive compu-

tational bioinformatics analysis to illuminate these afore-

mentioned issues. Likewise study regarding the pattern of

expression of SOD isoenzymes genes along with leaf

development has not been done yet. Hence, we did in silico

study as well as quantitative real time-polymerase chain

reaction (qRT-PCR) to analyze the differential expression

patterns of SOD genes along leaf developmental stages

using rice as model plant.

Materials and methods

Database search and sequence analysis and subcellular

localization of SOD isoenzymes

To identify the SOD isoforms in an indica-type rice (Oryza

sativa L. cv. Dong-jinbyoe), we conducted a database

search with resources from the National Center for Bio-

technology Information (NCBI; www.ncbi.nlm.nih.gov).

Our results were further verified by a putative function

search via the public database from the Rice Genome

Annotation Project (RGAP; http://rice.plantbiology.msu.

edu/cgi-bin/putative_function_search.pl). The protein

sequence homology search was performed with the Clu-

stalW program (www.ebi.ac.uk/clustalw/). To observe the

phylogenetic relationships among SOD isoenzymes, we

drew a phylogram with the Molecular Evolutionary

Genetics Analysis tool (MEGA v4.1; Tamura et al. 2007),

using 1,000 replicates for boot-strapping. The phylogram

was generated by the neighbor-joining (NJ) method and

viewed by the NJ Plot program. Sub-cellular localizations

of proteins, based on the presence of N-terminal proximal

amino acid sequences, were predicted using the TargetP1.1

server at the Technical University of Denmark (http://

www.cbs.dtu.dk/services/TargetP/). In addition, to verify

those predictions, we employed a Subcellular Proteomics

Database (SUBA; http://suba.plantenergy.uwa.edu.au), and

ARAMEMNON software (http://aramemnon.botanik.uni-

koeln.de/resrc_view.ep). The strong software ARAME-

NON can brings almost all predictors into one common

place by interlinking more than 17 computational servers

for bioinformatics programs in order to predict the possible

sub-cellular localization of any unknown protein.

In silico expression of rice SOD isoenzyme genes

at various developmental stages

We analyzed in silico spatio-temporal gene expression of

rice SODs over the entire period of field growth, using the

RiceXPro v1.6 tool (Sato et al. 2011) available from the

RGAP databases. Default-setting parameters were used and

the output was obtained in the form of graphs. The time

frame covered 13 to 125 days after transplantation.

Plant material and growing conditions

Rice seeds were first sterilized for 30 min with 50 %

Clorox, followed by washing for 5 min with 70 % ethanol

at least 3 times or until the Clorox smell disappeared.

Afterward, the seeds were rinsed at least thrice in sterile,

triple-distilled water for 10 min. They were then sown in

earthen pots containing an autoclaved soil mixture.

Growing conditions in the greenhouse included long days

(16 h photoperiod) at 28 �C/20 �C (day/night) and a light

intensity of 500 lmol photons m-2 s-1.

Extraction of RNA and cDNA synthesis

To examine the differential gene expression of SOD genes

in rice, we isolated total RNA as described by Nath et al.

(2008). Briefly, the third leaves from 10, 30, 55 and

80 days old plants were harvested and immediately frozen

in liquid nitrogen. To eliminate DNA from the RNA pool,

we added 2 lL of RNase-free DNase (20 mg mL-1 of

stock) and incubated this for 30 min at 37 �C. After

denaturation for 10 min at 70 �C, the DNase was removed

by a phenol-chloroform treatment and the samples were

used for further experiments. The cDNA strand was syn-

thesized from total RNA extracted from 10, 30, 55 and

80 days old third leaves of rice. In all, 5 lg of RNA was

denatured along with 100 nM oligoT primer and cooled to

room temperature for primer annealing. Afterward, 1 X

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123

M-MuLV reverse transcriptase buffer, 10 U of RNA guard,

and 200 U of M-MuLV reverse transcriptase (Promega

Corporation, Madison, WI, USA) were added to the mix-

ture for synthesis of cDNA according to the manufacturer’s

instructions.

Analysis of differential pattern of SOD gene expression

by qRT-PCR

In the current study, qRT-PCR was performed with the

CFX96TM Real-Time system (Bio-RAD) and SYBR

Green Reagents (Applied Biosystems). Samples contained

5 lL of 19 SYBR Green Master Mix, 2 lL each of for-

ward and reverse primers of pM concentration, and 3 lL

synthesized cDNA to make the final reaction volume of

12 lL. We used Os-Actin1 gene for the internal control and

normalization to calculate fold changes in gene expression

of the seven SOD genes and one SOD copper chaperone.

All gene specific primers for SOD genes selected for qRT-

PCR are shown in Table 1.

Physical interactions of SOD isoforms

We used the STRING v9.0 tool (functional protein asso-

ciation networks; http://string-db.org/) to map physical

interactions, as well as to examine the inter- and intra-

networking among all six rice SODs and other cellular

proteins. This investigation, under default parameters,

involved information for known and predicted protein–

protein interactions.

Results

Bioinformatics search for SOD genes in Oryza sativa L.

and their localization

Sequences for SOD isoforms were obtained according to

annotations in the NCBI Gene Bank public database. We

identified total eight putative SOD genes in rice. This search

revealed two cytosolic copper-zinc SODs (cCuZn-SOD1 and

cCuZn-SOD2), one putative CuZn-SOD-like (CuZn-SOD-

L), one plastidic SOD (pCuZn-SOD), two iron SOD (Fe-

SOD2 and Fe-SOD3), and one manganese SOD (Mn-SOD1)

in the rice genome. One of them was found to be CuZn-SOD-

Chaperon (CuZn-SOD-CCh). To confirm this, we conducted

an extensive bioinformatics search for loci via RGAP, one of

the largest public rice databases. All predictions well mat-

ched between NCBI and RGAP. All eight genes revealed

considerable homology among themselves. Black and grey

shadowing indicates comparative conserved nature

(Fig. 1a). We speculate that these conserved amino acid

positions must be crucial to the proper functioning of SODs.

The phylogenetic tree, constructed on the background of

sequences, indicates that the genes could be grouped into

clearly defined clades, based on occurrence and function

(Fig. 1b). The eight SODs are grouped into two clades.

CuZn-SODs belong to the first clade and Mn-SOD1 and

Fe-SODs are grouped into the second clades. CuZn-SOD-

CCh exhibited highest divergence in phylogenetic analysis

in the first clade, because it is not an enzyme SOD but is

homologous to copper chaperones for SOD (Huang et al.

2012).

Table 1 SOD isoenzyme genes

and Os-Actin1-specific primer

pairs used for qRT-PCR

amplification

F forward primer, R reverse

primer

Gene Primer sequences Length (bps) GC content TM

cCuZnSOD1 F: 50-GAACCTTCCAGAAGCTCCAG-30 20 55 62

R: 50-CCCTTAACAATCTCACTGCTACC-30 23 47.8 62.5

cCuZnSOD2 F: 50-GAAGTGTCTCTGGGCTCAAG-30 20 55 61.9

R: 50-TGGCGGTTCTCATCTTGTG-30 19 52.6 62.1

CuZnSOD-L F: 50-CCTACAGATTTCACTAAGCGGG-30 22 50 62.3

R: 50-AGTCCAATGATACCGCATCC-30 20 50 61.8

CuZnSOD-CCh F: 50-TGTAGCTGAGTTCAAAGGGC-30 20 50 62.1

R: 5-TGACCATCCGTGTTTACCAG-30 20 50 61.8

pCuZnSOD F: 50-AAACAATTTGACGCACGGTG-30 20 45 62.2

R: 50-AGAATTTGGGCCACTCAGAG-30 20 50 61.9

MnSOD1 F: 50-GAAGGTATTCAAAAGTCGTGGC-30 22 45.5 61.7

R: 50-ATAAGGTTCCAGGGCATCAAG-30 21 47.6 62.1

FeSOD3 F: 50-TGTACTCCAGTGTGCCAATG-30 20 50 62.1

R: 50-TCCTCATCCATTTCAGCATCG-30 21 47.6 62.3

FeSOD2 F: 50-ATAACCTCAAGCCTATCAGCG-30 21 47.6 61.8

R: 5-ACCCATCCAGATCCTTGTAAAG-30 22 45.5 61.8

OsActin1 F: 50-GTATCCATGAGACTACATACAACT-30 24 40 62.1

R: 50-TACTCAGCCTTGGCAATCCACA-30 22 50 61.6

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Localizations for the SOD proteins were predicted on the

basis of their N-terminal proximal sequences. Tabulation and

annotation allowed us to group these isoforms as either a

chloroplast transit peptide (cTP), mitochondrial targeting

peptide (mTP), secretory pathway-signaling peptide (SP) or

others. The TargetP 1.1 tool clearly revealed pCuZn-SOD,

Fig. 1 Multiple sequence alignments and phylogram of eight SOD

genes in rice. a Alignments were made via ClustalW and highlighted

by Box Shader tool. Black and grey shadowing indicates comparative

conserved nature. All CuZn-SOD isoenzymes (cytosolic and plasti-

dic) were more conserved while those for Mn-SOD and Fe-SOD were

less conserved. b Phylogram of clustered CuZn-SODs, with cytosolic

genes sharing close homology that suggests more functions in

common. Fe-SOD2 and Fe-SOD3 exhibited highest divergence in

phylogenetic analysis. CuZn-SOD-CCh is shown as a junction

between CuZn-SODs and Mn- and Fe-SODs clusters

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CuZn-SOD-CCh and Fe-SODs as chloroplast target isoen-

zymes, whereas Mn-SOD1, cCuZn-SODs and CuZn-SOD-L

were localized to either the mitochondria, secretory pathways

or others (Table 2). This software prediction was verified by

comparing the sub-cellular localizations of their isoforms in

Arabidopsis thaliana, using the ARAMEMNON computa-

tional tool and MBT. Our NCBI and MBT searches predicted

the existence of all SODs in both rice and A. thaliana. We

noted with interest that the MBT annotation report had also

suggested the two isoforms of Mn-SOD1 as being mito-

chondrial and both cCuZn-SODs and CuZn-SOD-L as SP

(Fig. 2). Consistent with MBT prediction, the SUBA3 pre-

dictors again localized cCuZn-SOD1 and cCuZn-SOD2 to the

cytosol, CuZn-SOD-L to the peroxisome and Mn-SOD1 to the

mitochondria (Fig. 2).

In silico expression of isoenzyme genes during plant

development

Using RGAP databases, we produced developmental stage-

dependent in silico expression patterns for eight SOD genes

(Fig. 3). We see that the level of transcripts changes at var-

ious stages of leaf development. Interestingly, the SOD

isoforms that are close on phylogenetic tree showed similar

temporal gene expression patterns. For example, both

cCuZn-SOD1 and cCuZn-SOD2 that are close in phyloge-

netic tree (Fig. 1b) showed increased level of gene expres-

sion during the vegetative stages (up to 80 days) and

decreased later onwards. Owing to high expression of

cCuZn-SODs in young leaves, we speculate that cCuZn-

SODs were particularly important throughout the whole

vegetative stages. However, we also observed that these

cCuZn-SODs were necessary during early flowering stages

with expression being detected for up to 80 days after

transplantation. The activity of Fe-SODs was very low in the

early developmental stages, started to increase with age from

the late vegetative stage and reached the peak at the age of

85 days and then started to decrease rapidly suggesting some

possible roles in matured leaves. The expression patterns of

Mn-SOD1 and CuZn-SOD-CCh were basically similar to

those of cCuZn-SODs. An interesting pattern was observed

in the expression of pCuZn-SOD, which showed very high

level of expressions at the very early stage of development

and at the late flowering stage. We speculated that the dif-

ferential gene regulation is meant for the need for different

optimum proportion of various scavenging SOD isoenzymes

for various developmental stages of leaf.

Differential expression of rice SOD genes in vivo

We conducted qRT-PCR to quantify the normalized expre-

ssion of eight SOD genes and analyze the change in gene

expression at 10 30, 55 and 80 days. The qRT-PCR data also

showed the differential expression of eight SOD mRNA in rice

along aging (Fig. 4). Generally, most of the expression patterns

were similar to those predicted from in silico analysis. Both

cCuZn-SOD1 and cCuZn-SOD2 showed high levels of gene

expression during the vegetative stages (up to 55 days) and

decreased thereafter. The activity of both Fe-SOD2 and

Fe-SOD3 were very low in the early developmental stages,

started to increase with age reaching their peaks at the age of

55 days and then started to decrease rapidly. Although in silico

analysis suggested very high expression of pCuZn-SOD at the

very early stage of development and at the late flowering stage

(Fig. 3d), its expression pattern shown in Fig. 4d was quite

different. Interestingly, unlike in silico analysis, qTR PCR

experiment reveals that the expression of CuZn-SOD-L showed

its maximum at 10 days and constantly decreased along leaf

age (Fig. 4e). Overall, our results suggested that all of these

isoforms are required in different proportions within the plant

system, such that they are expressed differentially, even under

control conditions.

Table 2 Summary of subcellular localization for SOD isoenzymes in rice

Isozyme Gene ID Amino acid length TargetP score for sub-cellular localization Predicted localization

RAGP Accession cTP mTP SP Others

cCuZn-SODl LOC_Os03g22810 L36320 271 0.132 0.29 0.034 0.436 Cytosol

cCuZn-SOD-2 LOC_Os07g46990 D01000 153 0.194 0.059 0.295 0.433 Cytosol

CuZn-SOD-L LOC_Os03gll960 AK073785 165 0.056 0.21 0.231 0.322 Peroxisome

pCuZn-SOD LOC_Os08g44770 D85239 212 0.747 0.029 0.233 0.009 Chloroplast

CuZn-SOD-CCh LOC_Os04g48410 AK110034 313 0.706 0.08 0.098 0.003 Chloroplast

Mn-SODl LOC_Os05g25850 L34038 232 0.004 0.544 0.715 0.015 Mitochondria

Fe-SOD3 LOC_Os06g05110 AB014056 256 0.891 0.346 0.035 0.028 Chloroplast

Fe-SOD2 LOC_Os06g02500 AK111656 392 0.891 0.052 0.017 0.015 Chloroplast

Specific gene locus numbers and accession numbers were collected from and RGAP and NCBI databases, respectively. Subcellular localizations

were predicted from the TargetP1.1 server

cTP chloroplast transit peptides, mTP mitochondrial targeting peptides, SP secretory signaling pathway peptides

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Bioinformatics analysis of physical interactions

among SOD isoforms

Interactions among the five major SOD isoenzymes and

with other cellular components were mapped in silico

(Fig. 5). pCuZn-SOD showed an interaction with Fe-

SOD2, and the latter also interacted with both cytosolic

CuZn-SOD isoforms. As expected, cCuZn-SOD1 and

cCuZn-SOD2 interacted with each other. These tight links

among the cCuZn-SODs, pCuZn-SOD, and Fe-SODs

suggested that their co-regulation and co-expression are

required for the scavenging of ROS generated during the

various stages of leaf development. Mn-SOD interacted

with cCuZn-SOD-2, either directly or via catalase isoen-

zyme-A. It also showed interactions with the catalase

domain-containing protein, catalase isoenzyme-A and B,

fumarate hydratase, proxiredoxin-1 and 2, and pullulanase

precursor proteins. This implied that its localization is

Fig. 2 Computational method to predict sub-cellular localization of

SOD isoenzymes in Arabidopsis thaliana, using multiple bioinfor-

matics tools. Strong ARAMEMNON software was utilized to

combine more than 17 predictor servers into one common place in

order to predict localization at cellular level (left and right panels).

Middle-panel prediction was made via SUBA server

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diverse, occurring in the mitochondria and within secretory

pathways.

Discussion

In this study, we analyzed the expression of seven SOD

genes and a copper SOD chaperone gene during develop-

mental stages of rice. Our sub-cellular localization analysis

revealed that rice has two cytosolic forms of cCuZn-SODs,

one peroxisomal form of CuZn-SOD-L, one plastidic form

of pCuZn-SOD, one mitochondrial form of Mn-SOD1 and

two plastidic forms of Fe-SODs. In addition, a CuZn-SOD

chaperone, CuZn-SOD-CCh was a plastidic form.

We have found considerable matching between our in

silico and in vivo experimental gene expression data for

cCuZn-SODs and Fe-SODs. Two cCuZn-SODs were found

in rice, although only one cCuZn-SOD is reported in

Arabidopsis (Huang et al. 2012). In rice the expression

levels of cCuZn-SODs were high throughout the whole

Fig. 3 In silico expression

profile of eight SOD genes in

rice leaves using RGAP

databases with default

parameters. Expression of

cCuZn-SODs was greatest

during early stage of

development while that for

Fe-SOD was during late

83–90 days after

transplantation. cCuZn-SODs

were expressed throughout

other stages of leaf and grain

development, with expression

being detected for up to 80 days

after transplantation,

particularly cCuZn-SOD1.

Mn-SOD and pCu-Zn-SOD were

expressed low over entire

developmental period

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vegetative stage of rice and dropped significantly at the

early flowering stage (Figs. 3a, b, 4a, b). Organelles with a

highly oxidizing metabolic activity or with an intense rate

of electron flow are major sources of ROS production, and

chloroplasts, mitochondria and microbodies are examples

in plant cells (Mittler et al. 2004). These cCuZn-SODs may

play an important role to protect from ROS generated from

active mitochondrial activities during germination of seeds

or early development of seedlings, and support to this

possibility comes from results showing a lower germina-

tion rate in the Arabidopsis cCuZn-SOD deficient mutant

(Huang et al. 2012). The high expression of these genes

throughout the whole vegetative stage also indicates their

role for the protection of ROS generated from chloroplasts

during active photosynthesis under high light and r various

stress conditions in the light.

As mentioned above, our in silico and in vivo experi-

mental gene expression data for Fe-SODs were very sim-

ilar, and even the expression patterns of Fe-SOD3 and Fe-

SOD2 were also very similar with each other (Figs. 3g, h,

4g, h). In Arabidopsis three Fe-SODs are reported, but only

two forms (FSD2 and FSD3) were in plastids (Myouga

Fig. 4 Differential expression

patterns of eight SOD genes by

qRT-PCR analysis in mature

rice leaves sampled at 10, 30, 55

and 80 days after

transplantation. Os Actin1

served as internal control and

normalization of transcript

level. The qRT-PCR data

revealed the differential

expression of eight SOD mRNA

during rice leaf development

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et al. 2008). In Arabidopsis FSD2 and FSD3 are known to

form a heterocomplex for SOD activity, and therefore very

similar expression patterns are very reasonable to be

accepted. Therefore, we can speculate that rice Fe-SOD2

and Fe-SOD3 also form a heterocomplex for SOD activity

in rice.

In Arabidopsis, FSD and FSD3 play essential roles in

early chloroplast development (Myouga et al. 2008), and

in silico analysis using Genevestigator (https://www.

genevestigator.com/gv/index.jsp) revealed that their

expression is high in the early developmental stages and

keep decreasing during plant development. However, their

expression was very low in the early developmental stages

and started to increase with age from the late vegetative

stage (Figs. 3g, h, 4g, h). Differences in the expression

pattern of Fe-SODs between rice and Arabidopsis remain

for further study.

Camp et al. (1990) have shown that Fe-SOD is mainly

expressed under adverse environmental or stressful condi-

tions, and Kliebenstein et al. (1998) reported that stresses

in the chloroplast can lead to enhanced Fe-SOD enzyme

activity. Moreover, Erturk (1999) and Alscher et al. (2002)

have found that stress treatments are associated with the

appearance of a second and a third Fe-SOD gel band,

suggesting the promotion of stress-induced expression or

activation. Considering above findings, we speculate that

Fig. 5 Physical interactions of

SOD isoenzymes. Pictogram

was generated by STRING tool.

pCuZn-SOD interacted with Fe-

SOD because both are localized

to chloroplasts. Fe-SOD also

interacted with both isoforms of

cytosolic CuZn-SODs; cCuZn-

SOD1 and cCuZn-SOD2 also

interacted with each other. Mn-

SOD interacted with cCuZn-

SOD2 either directly or via

catalase isoenzyme-A. Because

of its diverse localizations to

mitochondria, peroxisomes, and

secretory pathways, Mn-SOD

also interacted with several

cellular factors: catalase

domain-containing protein,

catalase isoenzyme-A and B,

fumarate hydratase,

proxiredoxin-1 and 2, and

pullulanase precursor proteins

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the expression of Fe-SOD might not be induced in our

natural growth conditions.

Fe-SOD is reportedly absent in many plant species,

especially monocots, and its presence is not obligatory

(Bridges and Salin 1981; Bowler et al. 1994). However,

several research groups have found evidence for this iso-

enzyme in the monocot rice (Pan and Yau 1991; Kaminaka

et al. 1999; Kim et al. 2004). Their findings were also

confirmed in our study via qRT-PCR. The primary

sequence, secondary and tertiary structure analysis

revealed that Mn and Fe-SOD to be structurally homolo-

gous to each other (Parker and Blake 1988; Dehury et al.

2012). Due to this similarity, some in silico site identify the

Fe-SOD2 in this study as a Mn-SOD. The phylogenetic tree

demonstrated that Mn-SOD1 is much closer to Fe-SODs.

The in silico expression of pCuZn-SOD was very

interesting, because the level was very high in the early

stage of development and also in the late vegetative stage

(Fig. 3d). In silico analysis using Genevestigator revealed

that the expression pattern of Arabidopsis homologue is

very similar to that of rice homologue. However, the result

from our qRT-PCR experiment shows a different expres-

sion pattern (Fig. 4d), and this discrepancy remains for

further study.

There have been controversies regarding the localization

of SODs. CuZn-SODs are thought to be localized to the

chloroplasts (Ogawa et al. 1995), cytosol (Bowler et al.

1994) and peroxisomes and apoplasts (Corpas et al. 2006).

In our in silico analysis utilizing MBT and SUBA3,

cCuZn-SOD1 and cCuZn-SOD2 are verified to be cytosolic

isoforms (Fig. 2; Table 2). Furthermore, we determined

that pCuZn-SOD and Fe-SODs are targeted to the chloro-

plasts while Mn-SOD is mitochondrial. Our localization

predictions for Fe-SODs and Mn-SOD are different from

those by Bowler et al. (1994) and Fernandez-Ocana et al.

(2011) which assign Fe-SOD2 as Mn-SOD1.

In summary, we examined differential gene expression

of seven SOD genes and one SOD copper chaperone gene

in rice and have combined several analytical approaches to

gain insights into their role during plant development from

seed germination to early flowering stage. Based on in

silico analysis we can predict their roles during late flow-

ering stage and seed maturation and even senescing stage.

In silico prediction of the localization of each SOD gene

and protein interaction network analysis will help us to

understand the role of each SOD gene in detail. Further

works should be done in order to quantify the protein level

and check whether there holds correlation between corre-

sponding level of gene and protein expression. However,

owing to the lack of specific antibodies against SOD iso-

enzymes, we could not investigate their protein level at the

moment. Also, the results of this study, obtained from rice

grown in natural growth conditions, can be treated as

references in order to compare the expression of SOD

isoenzyme genes under various stress conditions. This

study tempts us to speculate that different proportions of

the SOD genes expression are required in rice from early

development to aging.

Acknowledgments This work was supported by a 2-year research

grant from Pusan National University. The authors are grateful for the

diligent and thorough critical reading of the manuscript by Dr. Saman

Seneweera, a senior scientist in the Department of Plant Physiology

and Biochemistry, University of Melbourne, Australia.

Conflict of interest The authors declare no conflict of interest.

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