Development of SYBR Green I-Based One-Step Real Time RT-PCR Assay for Quantifying Southern rice black-streaked dwarf virus in Rice

ORIGINAL ARTICLE

Development of SYBR Green I-Based One-Step Real Time RT-PCRAssay for Quantifying Southern rice black-streaked dwarf virusin RiceTong Zhou*, Linlin Du*, Ying Lan, Feng Sun, Yongjian Fan and Yijun Zhou

Institute of Plant Protection, Diagnosis and Detection Center of Plant Virus Disease, Jiangsu Academy of Agricultural Sciences, Jiangsu Province,

Nanjing 210014, China

Keywords

one-step real time RT-PCR, quantitation,

Southern rice black-streaked dwarf virus,

SYBR Green I

Correspondence

Y. Zhou and T. Zhou, Jiangsu Academy of

Agricultural Sciences, Nanjing, China.

E-mails: [email protected]; zhoutong@jaas.

ac.cn

*These authors contributed equally to this

work.

Received: March 15, 2013; accepted: June 13,

2013.

doi: 10.1111/jph.12152

Abstract

Southern rice black-streaked dwarf virus (SRBSDV) causes southern rice

black-streaked dwarf and maize rough dwarf diseases, which lead to

severe yield losses of crops in Southeast Asia. We report here a SYBR

Green I-based One-Step Real Time RT-PCR assay for quantifying SRBSDV

in rice rapidly and accurately. Primers used for assay were designed from

the conserved sequence in S9 RNA among SRBSDV isolates. The RNA

standards targeting the S9 region were obtained by transcription in vitro

for generation of a standard curve. The assay developed in this study was

found to be 100 times more sensitive than the conventional RT-PCR for

SRBSDV detection. The primers were very specific for SRBSDV. This study

clearly demonstrated the potential usefulness of developed assay for

detection and quantitation of SRBSDV in rice samples.

Introduction

Southern rice black-streaked dwarf virus (SRBSDV) is a

new species in the genus Fijivirus Group 2 within the

family Reoviridae (Zhang et al. 2008; Zhou et al. 2008;

Wang et al. 2010), which is transmitted efficiently to

rice and maize by the white backed planthopper

(WBPH, Sogatella furcifera) in a persistent manner (Pu

et al. 2012). Outbreaks of SRBSDV have caused signifi-

cant crop losses in Southern Asia. In 2009, SRBSDV

caused severe losses in North Vietnam, the winter hab-

itat of WBPH (Cuong et al. 2009; Guo et al. 2010), and

in China, over 30 million ha of rice field were infected

by SRBSDV and 6500 ha of crops failed (Zhou et al.

2010a). In 2010, over 120 million ha of rice were

infected by SRBSDV in China, which was 3.5 times

more than the previous year, suggesting rapid spread

andmajor losses in future years (Zhong et al. 2011).

SRBSDV isolated was indistinguishable in symp-

tomatology, the shape of virus particles and serologi-

cal properties from Rice black-streaked dwarf virus

(RBSDV) and was therefore initially considered to be

an isolate of RBSDV (Ruan et al. 1984; Zhou et al.

2004, 2008; Zhang et al. 2008). The pathogen of this

disease was not identified until 2008, which was first

observed in Yangjiang, Guangdong province in China

in 2001 (Zhou et al. 2010a).

In order to further study and achieve the ultimate

aim of forecasting and controlling the spread of south-

ern rice black-streaked dwarf disease, the diagnosis of

SRBSDV has been improved remarkably with the

application of rapid molecular diagnostic systems,

such as direct observation of typical symptoms (Zhou

et al. 2008), Reverse Transcript-Polymerase Chain

Reaction (RT-PCR) (Zhou et al. 2008, 2010b; Ji et al.

2011; Wang et al. 2012a; Dot-Enzyme-Linked Immu-

nosorbent Assay (Dot-ELISA) (Wang et al. 2012b)

and Reverse Transcription Loop-Mediated Isothermal

Amplification (RT-LAMP) (Zhou et al. 2012). How-

ever, some methods are time consuming and inaccu-

rate, and some especially cannot precisely quantify

the copy numbers of SRBSDV RNA.

� 2013 Blackwell Verlag GmbH 1

J Phytopathol

The one-step real time RT-PCR assay has many

advantages over conventional detection methods,

including rapidity, quantitative detection, lower con-

tamination rate, higher sensitivity and specificity. It has

already proved to be efficient for the detection of plant

RNA and DNA viruses. Here, a sensitive and reliable

one-step real time RT-PCR assay was developed and

optimized for quantifying SRBSDV in rice, which also

provides a reliable basis for the further studies of patho-

genicmechanismandmolecular biologyof SRBSDV.

Materials and Methods

Plant material

Rice plants infected with SRBSDV were collected from

Hainan provinces of China in the growing seasons of

2010. The samples had been previously tested by

RT-PCR (Ji et al. 2011), and stored at �70°C.

Designing of primers

Based on the sequences of the highly conserved

regions of the SRBSDV genome, that were dissimilar

to those of RBSDV, the oligonucleotide primers were

designed using Primer 5 according to specific criteria.

The pair of primers for SRBSDV was as follow: SRB-

SDV-S9-F: GAGACCCAC CTCCACTGATT (upstream

Tm = 58°C) and SRBSDV-S9-R: ACGTTTACCACTGCG

CC TTC (downstream Tm = 58°C) correspond to the S9

of SRBSDV (GenBank Accession no. EU523359.1),

and were expected to amplify a fragment of 141 bp for

the positive sample.

Isolation of total RNA

Total RNA from rice stem (100 mg) was extracted

using TRIzol� Reagent (Invitrogen, Carlsbad, CA,

USA) according to the manufacturer’s protocols. In

the final step, the RNA was resuspended in 50 llDEPC-treated water. RNA concentration was deter-

mined by spectrophotometric analysis (Eppendorf

BioPhotometer plus). The integrity of RNA samples

was assessed by agarose gel electrophoresis.

Preparation of SRBSDV viral RNA standards

In order to construct the standard curve for quantify-

ing the number of SRBSDV copies in infected rice

tissue as well as to optimize the reaction system and

check the detection limit of the test system, RNA tran-

scripts were synthesized in vitro and purified for fur-

ther use. A 141 nucleotide cDNA fragment from the

SRBSDV S9 gene was cloned into pGEM-T easy vector

(Promega, Madison, WI, USA) according to the manu-

facturer’s instructions, and transformed into compe-

tent cells of Escherichia coli strain DH5a.The presence

of inserted PCR products was monitored by gel elec-

trophoresis of restriction enzyme cleavage, PCR

screening and sequence assay. Purified plasmid DNA

was measured by spectrophotometric analysis

(Eppendorf BioPhotometer plus), then linearized by

vector specific restriction enzyme. Positive strand

RNA was transcribed using the T7 Transcription Kit

(Fermentas, Shenzhen, China) according to the man-

ufacturer’s specification, using 1 lg of linearized plas-

mid DNA as template. RNA was treated with 4U of

DNase I (Fermentas) for 15 min at 37°C to remove

the remaining DNA followed by inactivation of DNase

I at 65°C for 10 min, purified using EZ-10 Spin Col-

umn 5 min RNA Cleanup&Concentration Kit (Bio

Basic Inc., Ontario, Canada). The amount of RNA

standard was determined by spectrophotometric (Ep-

pendorf BioPhotometer plus) reading and converted

to molecular copies by using the following formula

(Krieg 1991).

One-step real time RT-PCR assay and optimization

One-step real time RT-PCR amplification was per-

formed on the Bio-Rad IQTM (Bio-Rad, Hercules, CA,

USA) 5 Multicolor Real-Time PCR Detection System.

The reactions were carried out using iScriptTM One-

Step RT-PCR Kit with SYBR Green (Bio-Rad) accord-

ing to the manufacturer’s instructions. The data were

analyzed with IQ 5 OPTICAL SYSTEM SOFTWARE Version 2.0

(Bio-Rad).

Protocol optimization was recommended for

developing a good one-step real time RT-PCR detec-

tion system. This procedure was carried out using

RNA resulted from in vitro transcription as described

above. In a total volume of 20 ll, the reaction mixture

contained 2 ll of RNA standards, 10 ll of 2 9 SYBR

Green RT-PCR reaction mix, 0.4 ll iScript reverse

transcriptase for one-step RT-PCR and nuclease-free

water with supplement. The primer was introduced

initially at 300 nM in real time RT-PCR reactions

according to the manufacturer’s recommendations. In

order to obtain the optimum concentration to

Copy number ðcopies=lLÞ ¼ concentration ðg=lLÞ � 6:02 � 1023

transcript length ðbpÞ � 340

� 2013 Blackwell Verlag GmbH2

SYBR GREEN I-BASED ONE-STEP REAL TIME RT-PCR T. ZHOU ET AL.

increase the sensitivity and specificity, the upstream

and downstream primers were subjected to an optimi-

zation of concentration using a 5 9 5 matrix of 100,

200, 300, 400, and 500 nM for each concentration of

primer. The optimum primer concentration was

found to be 300 nM for both upstream and down-

stream primers, the same as the manufacturer’s rec-

ommendations.

The parameters of the reaction program were also

examined to determine the most suitable program.

Annealing-extension temperature was optimized by

55–65°C. The most suitable annealing-extension tem-

perature was 60°C. The reaction protocol consisted of

cDNA synthesis at 50°C for 10 and 5 min of reverse

transcriptase inactivation at 95°C, followed by 40

cycles of denaturation/annealing-extension (10 s at

95°; 30 s at 60°C). Following amplification, a melting

curve analysis was performed to verify the authentic-

ity of the amplified product by its specific melting

temperature (Tm). Melting curve analysis consisted of

a denaturation step at 95°C for 1 min, lowered to

55°C for 1 min, and followed by 80 cycles of incuba-

tion in which the temperature is increased from 55 to

95°C at a rate of 0.5°/10 s/cycle with continuous

reading of fluorescence.

Viral RNA transcripts, prepared as described above,

were used in 10-fold serial dilutions to generate stan-

dard curves and to compare the sensitivity of the assay

with RT-PCR.

In order to further verify the specificity of the assay,

total RNA from rice leaves infected with SRBSDV or

RBSDV was applied independently to the reaction

mix and amplified using the one-step real time

RT-PCR protocol. Viral RNA standards served as the

positive control.

RT-PCR

In order to determine the sensitivity of one-step real-

time RT-PCR assay, RT-PCR was performed with the

same primer sets targeting the 141 bp of the SRBSDV

S9 for comparison.

For the RT reaction, 1.2 lg of RNA standards,

0.65 lM of downstream primer and 7 ll of DEPC-trea-ted water were mixed in a tube, reactions were per-

formed in a final volume of 15 ll using M-MuLV

reverse transcriptase (200 U/ll; Fermentas) according

to the manufacturer’s instructions (Zhou et al. 2012).

The 25 ll PCR reaction carried out with 2 ll of

above RT product were performed on the S1000TM

Thermal Cycler (Bio Rad). The optimized program

was 94°C for 5 min; 35 cycles of 94°C for 45 s, 60°Cfor 45 s, and 72°C for 30 s; and a final extension at

72°C for 10 min. The PCR products were routinely

checked for purity and size by ethidium bromide

staining after agarose gel electrophoresis (2% agarose,

TAE) and sequenced to further verify that it repre-

sents the target DNA fragment.

Results

Standard curve

One-step real time RT-PCR assay for SRBSDV geno-

mic RNA was determined by using 10-fold serial dilu-

tions of the RNA standards ranging from 5.0 9 1010

to 5.0 9 104 copies/reaction (Fig. 1a,b) to ascertain

the detection limits of the one-step real time RT-PCR

method and the linearity of the assay. Ct-values were

measured and plotted against the known copy num-

bers of the standard sample. The standard curve cov-

ered a linear range of seven orders of magnitude. The

slope (�3.317) and the correlation coefficient

(R2 = 0.996) of the standard curve showed that this

assay could be used to quantify target RNA in infected

rice tissue.

Melting curve

Following amplification, a melting curve analysis was

performed to verify the correct product by its specific

melting temperature. Melting curve with IQ 5 OPTICAL

SYSTEM SOFTWARE Version 2.0 showed that SRBSDV S9

gene specific amplicon melts at 78°C (77.5–78.5°C).The dissociation plots (Fig. 2) showing the SRBSDV

specific melting temperature (Tm = 78°C) revealed

the one-step real time RT-PCR was specific for

SRBSDV.

The results of specificity further verify that the

primers were absolutely specific for SRBSDV. The

viral RNA standards (Fig. 3, lane 1) and total RNA

extracted from rice leaf infected with SRBSDV (Fig. 3,

lanes 2–9) could be easily detected and quantified. In

contrast, the rice leaf tissue carrying RBSDV (Fig. 3,

lanes 10–11) was not detectable.

Comparison of sensitivity between RT-PCR and

one-step real time RT-PCR

In order to evaluate the sensitivity between one-step

real time RT-PCR assay and RT-PCR in SRBSDV

detection, a series of 10-fold dilutions of standard

ssRNA ranging from 6.4 9 1010 to 64 copies were

tested using the two detection techniques. Positive

one-step real time RT-PCR amplifications were

observed up to dilutions of 64 copies (Fig. 4a), while


T. Zhou et al. SYBR GREEN I-BASED ONE-STEP REAL TIME RT-PCR

in the RT-PCR, product amplification was seen up to

dilutions of 6.4 9 103 copies, as indicated by the pres-

ence of 141 bp amplicon after agarose gel electropho-

resis (Fig. 4b). The negative control did not show a

consistent or detectable product yield by either assay.

Comparing the results, the one-step real time RT-PCR

assay was 100 times more sensitive than the RT-PCR

for SRBSDV detection.

Discussion

The disease caused by SRBSDV has recently became

one of the most damaging rice crop disease in South-

ern China and Vietnam and led to significant eco-

nomic loss (Zhang et al. 2008; Zhou et al. 2008,

2012). Rice plants infected with SRBSDV show no

symptoms in the latent period of infection and is

difficult to diagnose at an early stage, but is very

destructive at a late stage. Therefore, these diseases

need to be monitored and diagnosed at their early

stages for effective mitigation of loss and risk assess-

ment of infected rice paddy field (Hoang et al. 2011;

Zhou et al. 2012; Zhang et al. 2013).

Therefore, accurate and efficient detection of patho-

gens is critical for forecasting and controlling the

spread of disease. So far, RT-PCR is given priority to the

accurate diagnosis of SRBSDV (Zhou et al. 2008,

2010b; Ji et al. 2011; Wang et al. 2012a). In addition

to conventional RT-PCR, more rapid and sensitive

assays, such as dot-ELISA (Wang et al. 2012b) and

RT-LAMP (Zhou et al. 2012), have been reported.

Although immunoassays are more economical and

(b)

(a)

Fig. 1 Standard curve for SYBR Green I-based

one-step real time RT-PCR amplification of

standard SRBSDV ssRNA (viral transcripts). (a)

Amplification plots showing the testing in

duplicate of a 10-fold dilution series containing

standard ssRNA ranging from 5.0 9 1010 to

5.0 9 104 copies/reaction. The threshold (T)

of normalized reporter fluorescence used for

Ct calculation is represented with a black hori-

zontal line. (b) Standard curve showing a linear

relationship between standard ssRNA concen-

trations and Ct. Plots are Ct-values vs. log stan-

dard ssRNA concentrations (copies/reaction)

generated from mean data of experiments

performed in triplicate.



better suited for large numbers of samples (Manoharan

et al. 2004), the detection efficiency is limited by the

specificity of antibody. As the outer capsid of SRBSDV

particles is very fragile, and the virus is present in very

low titers only in the phloem of the host plants (Zhou

et al. 2008, 2010b), it is very difficult to obtain the spe-

cific antibody by virion purification. Wang et al.

(2012b) established a Dot-ELISA assay for the detec-

tion of SRBSDV, but they did not refer to whether this

method could be used to detect SRBSDV from the vec-

tor and distinguish between SRBSDV and RBSDV. Sun

et al. (2004), Yang et al. (2007) and Ouyang et al.

(2010) had obtained polyclonal antibodies of RBSDV,

another reovirus from the same genus Fijivirus group 2

by prokaryotic expression technology, but none of

them were widely used in the practical production for

the lower specificity and antibody titer (Zhou et al.

2010b). The nested RT-PCR (Zhou et al. 2008) has

high levels of sensitivity and specificity, but it is time

consuming as well as complex procedures.

In this study, SYBR Green I-based one-step real-

time RT-PCR method was developed for the detection

and quantification of SRBSDV in rice plants. The opti-

mal reaction system and the standard curve were

developed using the RNA standards synthesized by

transcription and purification in vitro. Under the opti-

mum conditions, the copy numbers of SRBSDV RNA

of samples could be quantified according to the stan-

dard curve within only 2 h. The decrease of threshold

for virus detection leads to an improvement of control

Fig. 2 Melting curve obtained with 10-fold

serial dilutions of the RNA standards.

Fig. 3 The specificity of the Real time RT-PCR

assay and detection of SRBSDV from rice sam-

ples collected from two provinces of China by

developed assy. lane 1,The viral RNA stan-

dards; lanes 2–9, total RNA extracted from rice

leaf infected with SRBSDV; lanes 10–11, total

RNA extracted from rice leaf infected with Rice

black-streaked dwarf virus.



schemes for plant virus diseases, especially for which

need to prevent and control by eradicating the early

infected plants and viruliferous vector insects (Zhang

et al. 2008). The method proved to be extremely sen-

sitive and specific for SRBSDV.

The protocol developed in this study appeared to be

suitable for detecting and quantifing total RNA of

SRBSDV from infected rice tissue of clinical samples.

The field samples from Guangzhou and Yunnan Prov-

ince successfully verified the practical applicability of

the developed assay. The considerable advantages of

quantifiability, specificity, accuracy compared with

other routine detection methods also make it a pow-

erful tool in basic research.

Acknowledgements

This research was supported by grants from the

National Natural Science Fund (31101412), Jiangsu

Agricultural Scientific Self-innovation Fund (cx [12]

5007; cx [12]1003), Special Fund for Agro-scientific

Research in the Public Interest (No.201303018) and

Jiangsu Province Science and Technology Support

Project (BE2012303).

References

Cuong HV, Hai NV, Man VT, Matsumoto M. (2009) Rice

dwarf disease in North Vietnam in 2009 is caused by

southern rice black-streaked dwarf virus (SRBSDV). Bull

Inst Trop Agric Kyushu Univ 32:85–92.

Guo R, Zhou GH, Zhang SG. (2010) Preliminary study on

occurring characteristics and control strategy of

Southern rice black-streaked dwarf virus, SRBSDV,

Genus Fijivirus. China Plant Prot 30:17–20.

Hoang AT, Zhang HM, Yang J, Chen JP, H�ebrard E, Zhou

GH, Vinh VN, Cheng JA. (2011) Identification, character-

ization, and distribution of southern rice black-streaked

dwarf virus in Vietnam. Plant Dis 95:1063–1069.

Ji YH, Gao RZ, Zhang Y, Cheng ZB, Zhou T, Fan YJ, Zhou

YJ. (2011) A simplified method for quickly detection of

rice black-streaked dwarf virus and southern rice

black-streaked dwarf virus. Chinese J Rice Sci 25:91–

94.

Krieg PA. (1991) Improved synthesis of full length RNA

probe at reduced incubation temperatures. Nucleic Acids

Res 18:6463.

Manoharan S, Parthiban M, Prabhakar TG, Ravikumar G,

Koteeswaran A, Chandran NDJ, Rajavelu G. (2004)

Rapid serological profiling by an immunocomb-based

dot-enzyme-linked immunosorbent test for three major

poultry diseases. Vet Res Commun 28:339–346.

Ouyang YL, Wu JX, Xiong RY, Zhou YJ, Zhou XP. (2010)

Prokaryotic expression of coat protein gene S10 of rice

black-streaked dwarf virus, and preparation and applica-

tion of its polyclonal antibody. Chinese J Rice Sci

24:25–30.

Pu LL, Xie GH, Ji CY, Ling B, Zhang MX, Xu DL, Zhou GH.

(2012) Transmission characteristics of Southern rice

black-streaked dwarf virus by rice planthoppers. Crop

Prot 41:71–76.

Ruan YL, Chen SX, Lin RF, Jiang WL, Jin DD. (1984) Stud-

ies on rice black-streaked dwarf virus. J Zhejiang Agric

Sci 4:185–187.

Sun LY, Xu JL, Fang SG, Wang ZH, Han CG, Li DW, Yu

JL. (2004) Sequence analysis and prokaryotic expres-

sion of genomic segments 8 and 9 of rice black--

streaked dwarf virus isolated from maize. J Agric

Biotechnol 12:306–311.

Wang Q, Yang J, Zhou GH, Zhang HM, Chen JP, Adams

MJ. (2010) The complete genome sequence of two iso-

lates of southern rice black-streaked dwarf virus, a new

member of the genus Fijivirus. J Phytopathol

158:733–737.

Wang Q, Zhou GH, Zhang SG. (2012a) Detection of

Southern rice black-streaked dwarf virus using

one-step dual RT-PCR. Acta Phytopathol Sinica

42:84–87.

Wang ZC, Yu DD, Li XY et al. (2012b) The development

and application of a Dot-ELISA assay for diagnosis of

southern rice black-streaked dwarf disease in the field.

Viruses 4:167–183.

Yang J, Zhang HM, Chen JP, Dai LY. (2007) Prokaryotic

expression antiserum preparation and some properties

(a)

(b)

Fig. 4 The sensitivity of the real time RT-PCR assay (a) compared with

RT-PCR assay (b) M, DNA marker; lanes 1–10, 6.4 9 1010-64 copies/

reaction; NTC/11, Negative control.



of p8 protein of rice black-streaked dwarf Fijivirus. Acta

Phytophylacica Sinica 34:252–256.

Zhang HM, Yang J, Chen JP, Adams MJ. (2008) A

black-streaked dwarf disease on rice in China is caused

by a novel Fijivirus. Arch Virol 153:1893–1898.

Zhang P, Mar TT, Liu WW, Li L, Wang XF. (2013) Simulta-

neous detection and differentiation of rice black streaked

dwarf virus (RBSDV) and Southern rice black streaked

dwarf virus (SRBSDV) by duplex real time RT-PCR. Virol

J 10:24 (http://www.virologyj.com/content/10/1/24).

Zhong TR, Liu Y, Liu WC. (2011) In 2010, occurrence rea-

son and trend analysis of southern rice black-streaked

dwarf disease in China. China Plant Prot 31:32–

34.

Zhou GH, Xu DL, Li HP. (2004) Identification of rice

black-streaked dwarf virus infecting rice in Guangdong.

In: Peng YL. (ed.) Proceedings of the Conference on

Chinese Plant Pathology. Beijing, China Agricultural

Scientech Press, pp 210–212.

Zhou GH, Wen JJ, Cai DJ, Li P, Xu DL, Zhang SG. (2008)

Southern rice black-streaked dwarf virus: a new pro-

posed Fijivirus species in the family Reoviridae. Chin Sci

Bull 53:3677–3685.

Zhou GH, Zhang SG, Zou SF, Xu ZW, Zhou ZQ. (2010a)

Occurrence and damage analysis of a new rice dwarf

disease caused by southern rice black-streaked dwarf

virus. Plant Prot 36:144–146.

Zhou Q, Zhu JZ, Liang JG, Chen XY, Gao BD. (2010b)

Rapid detection of southern rice black-streaked dwarf

virus. Gen Appl Biol 29:1009–1012.

Zhou T, Du LL, Fan YJ, Zhou YJ. (2012) Reverse transcrip-

tion loop-mediated isothermal amplification of RNA for

sensitive and rapid detection of southern rice

black-streaked dwarf virus. J Virol Methods 180:91–95.



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Development of SYBR Green I-Based One-Step Real Time RT-PCR Assay for Quantifying Southern rice black-streaked dwarf virus in Rice