Simultaneous detection and differentiation of Rice black streaked dwarf virus (RBSDV) and Southern rice black streaked dwarf virus (SRBSDV) by duplex real time RT-PCR
© Zhang et al.; licensee BioMed Central Ltd. 2013
Received: 6 November 2012
Accepted: 14 January 2013
Published: 18 January 2013
The diseases caused by Rice black streaked dwarf virus (RBSDV) and Southern rice black streaked dwarf virus (SRBSDV) have been occurring epidemically in China and southeastern Asia in recent years. A sensitive, reliable and quantitative method is required to detect and distinguish for RBSDV and SRBSDV in rice and vector insects.
We developed a sensitive and lineage-specific duplex real time RT-qPCR for detection of RBSDV and SRBSDV in a single or/and double infection in rice samples. The duplex RT-qPCR was optimized using standard samples transcribed by T7 Large Scale RNA Production System in vitro. We developed a reliable system for duplex RT-qPCR, in which its co-efficiency of RBSDV and SRBSDV, were 91.6% and 90.7%, respectively. The coefficient of determination was more than 0.990; the slope of linear equation was −3.542, and −3.567, respectively. Out of 30 samples collected in North and Central China, which were suspected to be infected with these two viruses, 10 samples were detected RBSDV positive by RT-PCR and 12 samples by RT-qPCR. No mixed infections were found. Simultaneously, out of total 60 samples collected from Southern China, which were also suspected to be infected with these two viruses, 41 samples were determined SRBSDV positive by RT-PCR and 47 samples by RT-qPCR. Also in this case no mixed infections were found. The rice genes eEF-1a and UBQ5 were selected as internal controls for quantification assay also performed as good expression stability.
The duplex RT-qPCR assay provided as a sufficiently sensitive, specific, accurate, reproducible and rapid tool for the detection and differentiation of RBSDV and SRBSDV. The RT-qPCR assay can be used in routine diagnostic of these two viruses in order to study the disease epidemiology in rice crops.
KeywordsRBSDV SRBSDV RT-qPCR Discrimination Quantification
In major rice-growing countries, rice viral diseases have been occurring one after another and have inflicted widespread damage over huge areas. More than 15 rice viruses, especially planthopper or leafhopper transmitted viruses have reached epidemic proportions in many countries and have caused serious damage in rice. In China, major outbreak of Rice black streaked dwarf virus (RBSDV) was recorded after 1963, when double-cropping of rice became common in Southern China and total production started to greatly increase[2, 3]. A disease with similar symptoms of RBSDV was first observed in Guangdong Province, Southern China in 2001. The causal agent of the disease was identified as Southern rice black-streaked dwarf virus (SRBSDV), a tentative species in the genus Fijivirus, family Reoviridae. SRBSDV has recently spread throughout Southern China and Vietnam[5, 6]. The outbreak of SRBSDV in 2009 and 2010 caused serious yield losses in the Southern and Central region of China and in the Northern parts of Vietnam. Nearly 12 million hectares of domestic paddy fields were affected in 2010 in China. Currently, SRBSDV is also known to occur in a number of countries in Southeastern Asia, including Vietnam and Thailand[7, 8].
RBSDV occurs mainly in China, Japan and Korea. It is a member of the genus Fijivirus within the family Reoviridae[9, 10]. The virus is transmitted naturally to rice, maize, barley and wheat in a persistent propagative man-ner by three different species of planthopper, Laodelphax striatellus, Unkanodes sapporona and U. albifascia[11–13]. On the other hand, SRBSDV can be transmitted efficiently by the white-backed planthopper (Sogatella furcifera, Hemiptera: Delphacidae), which is not the main vector of RBSDV. Beside rice, maize (Zea mays), barnyard grass (Echinochloa crusgalli), flaccid grass (Pennisetum flaccidum) and Juncellus serotinus are also the hosts of SRBSDV[6, 14].
Both RBSDV and SRBSDV have similar genome structure containing with 10 segments of dsRNA that encoded at least six putative structural proteins (P1, P2, P3, P4, P8, and P10) and five putative nonstructural proteins (P6, P7-1, P7-2, P9-1 and P9-2)[4, 6, 10, 15]. Rice plants infected by either RBSDV or SRBSDV show typical stunting, dark green leaves and small enations on stem and leaf backs[7, 12]. However, sometimes these two viruses can be confused with each other and the disease is also very difficult to distinguish with the diagnostic based on symptoms, because the symptoms of these two diseases may vary according to the infection of different growth stages.
Some studies have reported successful methods of RBSDV and SRBSDV detection, including reverse transcription-polymerase chain reaction (RT-PCR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), indirect enzyme-linked immunosorbent assay (ELISA), and indirect dot-immunobinding assay (DIBA)[16–19]. Because information on the virus content in local fields is very important for forecasting and releasing warning schemes to advise farmers on the potential threat to their crops, a sensitive, reliable and quantitative method is required to detect and distinguish RBSDV and SRBSDV in rice and vector insects.
Nowadays, real-time PCR technology has proved an efficient tool for quantitative detection of many plant RNA and DNA viruses[20–25]. Here, we reported that the quantitative RT- qPCR method able to reliably discriminate and quantify RBSDV and SRBSDV in rice. This presented method will provide better possibilities for monitoring the virus numbers and contents in local fields and estimating the extent of primary infections, and then forecasting the outbreaks of these two rice viral diseases.
Standard curves of RT-qPCR
A standard curve of quantification of SRBSDV, eEF-1a, and UBQ5 gene in rice were developed respectively as described above (Figure1B, C, and D). According to the differences of original standard sample concentration, we used different copy ranges to determine the standard curves as follow: The linear ranges of SRBSDV, eEF-1a, UBQ5 were 106 – 102 copies, 106 – 102 copies, 106 – 102 copies respectively; the slope and correlation coefficient were −3.388, 0.986; -3.374, 0.994; -3.294 0.990, respectively.
Optimization of duplex RT-qPCR
Standard curves of duplex RT-qPCR
Detection and relative quantification of RBSDV or SRBSDV in rice samples
Detection of RBSDV and SRBSDV from rice samples collected from six provinces of China by RT-PCR and RT-qPCR
Number of samples
Duplex real-time RT-PCR positive
Duplex RT-PCR positive
North and central China
In this study, the minimum detection limit of this duplex RT-qPCR assay was 10 copies. We collected a total of 90 field rice samples showing dwarf symptoms from 6 provinces of China in 2012, 22 and 41 samples were detected as RBSDV infected by RT-PCR and RT-qPCR respectively. RBSDV was mainly detected in Northern and Central China (Shandong and Henan province). On the other hand, SRBSDV was detected in the samples collected from Southern China. Forty one and 47 samples were detected as SRBSDV infected by RT-PCR and RT-qPCR, respectively. So, this duplex RT-qPCR assay was able to detect more positive samples than RT-PCR.
The rice diseases caused by RBSDV and SRBSDV have been responsible for significant economic loss in recent years in China and other Asian countries. Diseases caused by RBSDV and SRBSDV were latent and difficult to diagnose at an early stage, but 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 assessment of infected rice paddy field[5, 6, 8]. RT-PCR, RT-LAMP, and serological methods are most commonly used for detecting plant viruses, but by none of these methods it is possible to determine a virus contents in plant and insects vector which are key factor for disease epidemics[17–19, 24]. In this study, we established a duplex RT-qPCR assay for the detection, discrimination, and quantification of RBSDV and SRBSDV in rice plants. Using two different fluorescence signals, this method could detect quantitatively RBSDV and SRBSDV in a one reaction tube at the same time. Comparing with RT-PCR, this assay showed higher specificity and sensitivity, and could be a useful method for epidemiological studing and forecasting and controlling the diseases (Table 1).
In RT-qPCR used in discrimination and quantification of several viruses[20, 24, 29], the Ct value is a parameter reflecting the quantity of template present in the reaction. Usually, lower Ct values indicate a high concentration of template and higher Ct values indicate a low concentration of template. This study showed that standard serial dilution curves were obtained with high RT-qPCR efficiency for RBSDV and SRBSDV (98.3 and 97.3%, respectively). The efficiency proved the balance among enzyme, dNTPs, primers and templates. In the duplex RT-qPCR, we got high co-efficiency of SRBSDV and RBSDV, which were 90.7% and 91.6%, respectively. The rationality of linear equation was determined by the coefficient of determination (R^2). Usually, R^2 value needs to be between 0 and 1, higher value indicates its higher rationality. In this study, the R^2 values of RBSDV and SRBSDV were 0.994 and 0.996 respectively. We therefore suggested that this duplex RT-qPCR could be used to detect quantitatively RBSDV and SRBSDV in routine virus diagnosis.
The rice UBQ5 and eEF-1a genes were selected as internal controls for quantification assay. UBQ5 and eEF-1a were the most stable across all the tissues and all growth stages examined as reference genes. RNA extraction errors, template loading deviations, and variations of reverse transcription efficiency could be eliminated from data analysis by quantification of the UBQ5 and eEF-1a genes. Simultaneously, the relative contents of RBSDV and/or SRBSDV in infected leaves of field samples could be determined by relative quantification.
Our results showed that the distribution of RBSDV and SRBSDV induced diseases were different in China. RBSDV induced disease was found in North and Central China (Shandong and Henan province), but SRBSDV mainly in Southern China (Hubei, Jiangxi, Hunan and Yunnan province). One of the reasons might be related to the biological characteristics of their vector insects. RBSDV is transmitted efficiently by small brown planthopper (L. Striatellus), which is believed to show strong indigenousness, overwinter as nymphs or eggs in most rice grown areas; feed on wheat plants in the spring, and migrate to rice seedling after wheat harvest, while SRBSDV can be transmitted exclusively by white backed planthopper (S. furcifera), a typical immigration pest not overwintering in most regions of China[33, 34]. The Southern China is on its immigration path and one of its overwintering regions[33, 35]. The abundances of this planthopper may cause break out of SRBSDV in Southern China and/or other Southeastern Asia countries. Although white-backed planthopper can migrate to Central and Northern China on the early or mid-August, rice plants reach a booting stage with higher resistance to virus infection.
Rice diseases induced by RBSDV and SRBSDV have caused a great loss in the South China and Southeastern Asia. A sensitive and quantitative method has been established to detect and distinguish two viruses in rice. Compared to RT-PCR, RT-qPCR is more sensitive and reliable. We proved that the specificity of primers/probes in the duplex RT-qPCR assay can effectively resolve the problem of mismatches and avoid false negatives and distinguish the RBSDV and SRBSDV. Using this technology, we could detect the possibly infected samples by only one virus or the two viruses at the same time. To the point, one requisite of RT-qPCR is to normalize the data with internal reference genes that is invariant regardless of treatment, such as virus infection, which takes into an account the potential error of RNA extract, template loading, and variation of reverse transcription efficiency. From the assay, we got that UBQ5 and eEF-1a were stable in this experiment. This study clearly demonstrated the potential usefulness of TaqMan probe based RT-qPCR assay for detecting and distinguishing of RBSDV and SRBSDV.
Materials and methods
Plant material and virus sources
Rice plants infected with RBSDV or SRBSDV were collected from Jiangsu and Guangzhou provinces of China in the growing seasons of 2008 and 2010 respectively. All the samples had been tested previously by RT-PCR, and stored at −70°C. Ninety field rice samples showing stunting, darkening of leaves, and waxy white galls along the veins on the underside of leaf blades and surface of sheaths were collected from Henan, Shandong, Hubei, Hunan, Jiangxi and Yunnan provinces of China in 2012, and stored in a freezer at −70°C.
Total RNA were extracted using the RNAiso Reagent (TaKaRa Dlian, China) as the protocol: grind the 0.1 g of leaf with the liquid nitrogen in the mortar, add 1 ml Trizol reagent to the power, put them at the normal temperature for 5 min; transform the liquid to the 1.5 ml tube, add 200 μl chloroform was added, the tubes were shaken for 15 s, lay aside 15 min at −20°C; centrifuged at 12000 rpm for 15 min; the supernatant was transferred into a new tube, equal isopropanol to supernatant was added and the samples were left at normal temperature 30 min; centrifuged 12000 rpm for 15 min; the precipitate was washed using 1 ml of 75% ethanol; the ethanol was removed at Rapid Glass Dryer; 40 μl DEPC H2O were added and the samples were stored at −70°C.
Only of the most critical points in the RT-qPCR experiment is to use only RNA of high purity and high integrity. The concentration of RNA was measured by NanaDrop-1000 (NanoDrop Technologies, USA). The 260/280 ratio should be between 1.9-2.1, and the 260/230 ratio should be greater than 2.0.
Primers and probes design
To the RBSDV, the first pair of primers of RBSDV: RBSDV 4-F: 5’- GCA AAC GCT CGT CAT CTA AG -3’ (upstream Tm = 56°C) and RBSDV 4-R: 5’-CCA CCA AAC GCT ATT TCA CT-3’ (downstream Tm = 56°C) correspond to the positive-sense strand of RNA4 of RBSDV (GenBank accession number AJ409146.1), and were expected to amplify a fragment of 903 bp for the standard sample. For fluorescence detection, one primer–probe combination was also selected from combinations proposed by the PRIMER EXPRESS software (Applied Biosystems, USA) according to the manufacturer’s instructions. The first primer–probe combination was designed: 2420 F:5’-CAT CAA AAA AGC CGG AAG CT-3’ (upstream Tm = 57°C), 2453 T:5’-CGT CAC TTT ACC ATT TGC TTG GCG ACA-3’ (TaqMan probe Tm = 70°C), and 2560R:5’-CAA CCA TGA TCC CTG TAA GAA TAA AA -3’ (downstream Tm = 57°C) targeting the conserved region within the positive-sense strand of RNA4 of RBSDV (GenBank accession number AJ409146.1). RBSDV probe was labeled at the 5’end with exachlorofluorescein (HEX, excitation wavelength 535 nm, emission wavelength 556 nm) and Black Hole Dark Quencher 1 (BHQ-1) at the 3’ end. The first pair of primers for SRBSDV: SRBSDV 4-F: 5’- ACG CTG ATA CCA ACA GAC CA -3’ (upstream Tm = 56°C) and SRBSDV 4-R: 5’- TTT AGC ACC AAG AAA GAC GA -3’ (downstream Tm = 54°C) correspond to the positive-sense strand of RNA4 of SRBSDV (GenBank accession number FN563992.1), and were expected to amplify a fragment of 1171 bp for the standard sample. For fluorescence detection, one primer–probe combination was selected from combinations proposed by the PRIMER EXPRESS software (Applied Biosystems, USA) according to the manufacturer’s instructions. The first primer–probe combination was designed: 1460 F: 5’- TGA AGT TTC AGA GCA CAT TCG AA -3’ (upstream Tm = 55°C), 1490 T: 5’- CGA AAG CCG TTT TCT CAG TCC TTA TGC A -3’ (TaqMan probe Tm = 70°C), and 1545R: 5’- CAC CTG GAA CTA AAG GCA AAG AA -3’ (downstream Tm = 61°C) targeting the conserved region within the positive-sense strand of RNA4 of SRBSDV (GenBank accession number FN563992.1). Primers and probes were purchased from Invitrogen Co. Ltd. SRBSDV probe were labeled at the 5’end with 6-carboxy-fluorescein (FAM; excitation wavelength 494 nm, emission wavelength 521 nm) and Black Hole Dark Quencher 1 (BHQ-1) at the 3’ end, respectively.
Simultaneously, we chose the Ubiquitin 5 and eEF-1a as the rice housekeeping genes, because of the highest stability across all the tissue samples examined. The pair of primers for rice ubiquitin 5 gene (GenBank accession number AK061988) is designed as follow: UBQ-F: 5’-CTC GCC GAC TAC AAC ATC C-3’ (upstream Tm = 56°C) and UBQ-R: 5’-AGG GCA TCA CAA TCT TCA CA-3’ (downstream Tm = 49°C) corresponding to nucleotides of the rice ubiquitin 5 gene, and were expected to amplify a fragment of 460 bp for the standard sample. The primer–probe combination: 533 F: 5’-AGT GCG GCC TCA CCT ACG T- 3’ (upstream Tm = 63°C), 557 T: 5’-ACC AGC AGG CTT AGG CGT AGG CT-3’ (TaqMan probe Tm = 75°C) and 581R: 5’-CCG CCC CCA AAG AAC AG-3’ (downstream Tm = 58°C) was designed to target the rice ubiquitin 5 gene as an internal control. TaqMan probe was labeled with 6-carboxyfluorescein (FAM, excitation wavelength 494 nm, emission wavelength 521 nm) at the 5’ end and Black Hole Dark Quencher 1 (BHQ-1) at the 3’ end. The pair of primers for the rice eEF-1a gene (GenBank accession number AK061464.1) was shown as follow: eEF-1a-F: 5’- GAC AAG ATT CCC TTC GTT CC -3’ (upstream Tm = 54°C) and eEF-1a-R: 5’- TGT AAA TAC CCG CAT TCC AC -3’ (downstream Tm = 55°C) corresponding to the sequence of the rice eEF-1a gene, and were expected to amplify a fragment of 945 bp for the standard sample. The primer–probe combination: 772 F: 5’- CCC AAG AGG CCA TCA GAC A - 3’ (upstream Tm = 53°C), 793 T: 5’- CCC CTG CGT CTT CCC CTT CAG G -3’ (TaqMan probe Tm = 69°C) and 840R: 5’- GCC AAT ACC ACC GAT CTT GTA CA -3’ (downstream Tm = 61°C) was designed to target the rice eEF-1a gene as another internal control. TaqMan probe was labeled with 6-carboxyfluorescein (FAM, excitation wavelength 494 nm, emission wavelength 521 nm) at the 5’ end and Black Hole Dark Quencher 1 (BHQ-1) at the 3’ end.
Preparation for viral RNA standards of one-step RT-qPCR
RNA transcripts were synthesized in vitro, inserting the cDNA fragments of RBSDV, SRBSDV, eEF-1a and UBQ-5 into the pGEM T-EASY (Promega, USA) respectively, and then transforming them into competent cell of trans 5a (Trans, China), The right inserted PCR products was monitored by gel electrophoresis of restriction enzyme cleavage.
Positive single strand RNA was transcribed using the RiboMAX Large Scale RNA Production Systems-T7 Kit (Promega, USA), using 2 μg linearzed plasmid DNA as template, then treated by DNaseI at 37°C for 20 min, purifying the RNA by RNAclean kit (BioTeke,China). The purified RNA was quantified using NanoDrop ND-1000.
One-step RT-qPCR assay and optimization for RBSDV, SRBSDV, UBQ5 and eEF-1a
One-step RT-qPCR reactions were performed in a final volume of 20 μl using the One-step PrimeScript RT-PCR Kit (TaKaRa Biotech., China) according to the manufacturer’s instructions. The reactions carried out with 2 μl of total RNA were performed on the Bio-Rad iCycler IQ Real-Time PCR Detection System. During the amplification process, the fluorescence intensity of the reporter dye (FAM or HEX) was recorded. These data allowed calculation of the normalized reporter signal, which was linked to the amount of product amplified. The threshold cycle (Ct-values, number of cycles for the fluorescence to reach the threshold) referred to the number of amplification cycles required for a significant increase in the reporter’s fluorescence. The data were analyzed with iCycler IQ Real-Time PCR Detection System Software.
Protocol optimization was recommended for developing a good RT-qPCR detection system. According to the manufacturer’s recommendations, the primer was introduced initially at 200 nM in RT-qPCR reactions. The upstream and downstream primers were subjected to an optimization of concentration using a 3 × 3 matrix of 100 nM, 200 nM, and 400 nM for each concentration of primer. This procedure was carried out using RNA resulting from in vitro transcription. The optimum concentration was found to be 200 nM for all upstream and downstream primers for the four assays. The concentration of the TaqMan probe was then optimized in order to reduce the quantity used in reactions. Detection of the RBSDV, SRBSDV, UBQ5 and eEF-1a target by RT-qPCR were efficient and reproducible with 400 nM, 200 nM, 200 nM, 200 nM TaqMan probes, respectively. The parameters of the reaction program were examined to determine the most suitable program. Different Tm was studied by gradient from 58°C to 63°C. The optimum Tm was 10 s at 60°C (the manufacturer’s recommendation was 10 s). The most suitable program and parameter was reverse transcription of the viral RNA at 42°C for 5 min. PCR performed with the hot-start Taq polymerase included an enzyme activation step (95°C for 5 s) followed by 40 cycles of denaturation/annealing–extension (10 s at 95°C; 30 s at 60°C).
Viral RNA transcripts, prepared as described above, were used in tenfold serial dilution to generate standard curves and to determine the assay efficiency and the quantification of viral target in the unknown samples.
Duplex RT-qPCR optimization
In order to avoid interaction, Probe and primer specific assay on different targets were prepared by the single RT-qPCR. To the specific of probe of RBSDV, We used standard sample of RBSDV (105 copies) as template, RBSDV-F/R as primer, SRBSDV-P as probe; to the control, standard sample of RBSDV (105 copies) as template, RBSDV-F/R as primer, RBSDV-P as probe, and then running the program. To the specific of probe of SRBSDV, We used standard sample of SRBSDV (105 copies) as template, SRBSDV-F/R as primer, RBSDV-P as probe; to the control, standard sample of SRBSDV (105 copies) as template, SRBSDV-F/R as primer, SRBSDV-P as probe, and then running the program. The program was that viral RNA Standard sample at 42°C for 5 min. PCR performed with the hot-start Taq polymerase included an enzyme activation step (95°C for 5 s) followed by 40 cycles of denaturation/annealing–extension (10 s at 95°C; 30 s at 60°C)
Simultaneously, primer specific assay for different targets was as follows: for the specificity of primer of RBSDV, we used standard sample of RBSDV (105 copies) as template, SRBSDV-F/R as primer, RBSDV-P as probe. As a control, standard sample of RBSDV (105 copies) as template, RBSDV-F/R as primer, RBSDV-P as probe, we run the program; for the specific of primer of SRBSDV, we used standard sample of SRBSDV (105 copies) as template, RBSDV-F/R as primer, SRBSDV-P as probe; as a control, standard sample of SRBSDV (105 copies) as template, SRBSDV-F/R as primer, SRBSDV-P as probe, we run the program. The program for transcription of the viral RNA was at 42°C for 5 min. PCR performed with the hot-start Taq polymerase included an enzyme activation step (95°C for 5 s) followed by 40 cycles of denaturation/annealing–extension (10 s at 95°C; 30 s at 60°C). The data were analyzed with iCycler IQ Real-Time PCR Detection System Software. According to the results of single RT-qPCR, the four segments have the same Tm, so we used the 60°C as the Tm value of duplex RT-qPCR. In the duplex reaction, every reaction contained the primers and probes of SRBSDV and RBSDV, we used standard sample of RBSDV (105 copies/μl) and H2O or SRBSDV (105 copies/μl) and H2O as template, respectively. The upstream and downstream primers were subjected to an optimization of concentration using a 3 × 3 matrix of 100 nM, 200 nM, and 400 nM for each concentration of primer. The range of concentration of the TaqMan probe was 100 nM, 200 nM, and 400 nM, respectively. The program for transcription of the viral RNA was at 42°C for 5 min. PCR performed with the hot-start Taq polymerase included an enzyme activation step (95°C for 5 s) followed by 40 cycles of denaturation/annealing–extension (10 s at 95°C; 30 s at 60°C). The data were analyzed with iCycler IQ Real-Time PCR Detection System Software.
Duplex RT-qPCR protocol
We have developed a following protocol for duplex RT-qPCR assay by One Step PrimerScript RT-PCR Kit (Takara, China) as follows: Each 20 μl reaction contained 2 μl of mixed RNA; 10 μl of 2x one Step RT-PCR Buffer III; 0.6 μl of TaKaRa Ex Taq HS; 0.6 μl of PrimeScript RT Enzyme MixII; 0.4 μl (200 nM), 0.4 μl (200 nM), 0.8 μl (400 nM) of SRB-F/R/P and 0.4 μl (200 nM), 0.4 μl (200 nM), 0.4 μl (200 nM) of RB-F/R/P; 3 μl of RNase Free H2O. The optimized program was 42°C 5 min; 95°C 10s, 95°C 5 s, 60°C 30 s, going over 40 cycles. Assays were performed on IQ2 real-time PCR system (Bio Rad, USA).
Viral RNA transcripts, prepared as described above, were used in 10-fold serial dilutions to generate standard curves and to determine the assay efficiency.
Financial support was provided by the National Key Basic Research of China (2010CB126200) and Nature Science Foundation of China (NSFC31071664).
- Hibino H: Biology and epidemiology of rice viruses. Annu Rev Phytopathol 1996, 34: 249-274. 10.1146/annurev.phyto.34.1.249PubMedView Article
- Cheng SX, Ruan YL, Jin DD, Cheng GY, Lin RF, Go DM: On the integrated control of rice dwarf disease in the second crop of rice. Acta Phytopathol Sin 1980, 7: 83-88. In Chinese
- Li DB, Wang GC, Cheng FJ: Epidemiological study on virus diseases and their control in Zhejiang Province. Acta Phytopathol Sin 1979, 9: 73-81. In Chinese
- Wang Q, Yang J, Zhou G, Zhang HM, Chen JP, Adams MJ: The complete genome sequence of two isolates of southern rice black-streaked dwarf virus, a new member of the genus Fijivirus. J Phytopathol 2010, 158: 733-737. 10.1111/j.1439-0434.2010.01679.xView Article
- Zhang HM, Yang J, Chen JP, Adams MJ: A black-streaked dwarf disease on rice in China is caused by a novel fijivirus. Arch Virol 2008, 153: 1893-1898. 10.1007/s00705-008-0209-4PubMedView Article
- Zhou G, Wen J, Cai D, Li P, Xu D, Zhang S: Southern rice black-streaked dwarf virus: a new proposed Fijivirus species in the family Reoviridae . Chinese Sci Bull 2008, 53: 3677-3685. 10.1007/s11434-008-0467-2View Article
- Zhou G, Zhang S, Zou S, Xu Z, Zhou Z: Occurrence and damage analysis of a new rice dwarf disease caused by southern rice black-streaked dwarf virus. Plant Prot 2010, 36: 144-146. In Chinese
- Hoang AT, Zhang HM, Yang J, Chen JP, Hébrard E, Zhou GH, Vinh VN, Cheng JA: Identification, characterization, and distribution of southern rice black-streaked dwarf virus in Vietnam. Plant Dis 2011, 95: 1063-1069. 10.1094/PDIS-07-10-0535View Article
- Shikata E CMI/AAB Descr Plant Viruses 1974, No. 125. In Rice black-streaked dwarf virus. England: Commonwealth Mycological Institute, Association of Applied Biologists, Kew, Surrey; 1974.
- Uyeda I, Kimura I, Shikata E: Characterization of genome structure and establishment of vector cell lines for plant reoviruses. Adv Virus Res 1995, 45: 249-279.PubMedView Article
- Shikata E, Kitagawa Y: Rice black-streaked dwarf virus: its properties, morphology, and intracellular localization. Virology 1977, 77: 826-842. 10.1016/0042-6822(77)90502-5PubMedView Article
- Chen SX, Zhang QY: Advance in researches on rice black-streaked dwarf disease and maize rough dwarf disease in China. Acta Phytophyl Sin 2005, 32: 97-103. In Chinese
- Wang ZH, Fang SG, Xu JL, Sun LY, Li DW, Yu JL: Sequence analysis of the complete genome of Rice black-streaked dwarf virus isolated from maize with rough dwarf disease. Virus Genes 2003, 27: 163-168. 10.1023/A:1025776527286PubMedView Article
- Zhou GH, Xu DL, Li HP: Molecular identification of the pathogen causing rice dwarf disease in Guangdong. In Proceedings of the 2004 Annual Meeting of Chinese Society of Plant Pathology. Beijing, China: Agricultural Sci-Tech Press; 2004:210-212. in Chinese
- Jia D, Chen H, Zheng A, Chen Q, Liu Q, Xie L, Wu Z, Wei T: Development of an insect vector cell culture and RNA interference system to investigate the functional role of fijivirus replication protein. J Virol 2012, 86: 5800-5807. 10.1128/JVI.07121-11PubMedPubMed CentralView Article
- Li L, Li H, Dong H, Wang X, Zhou G: Transmission by Laodelphax striatellus Fallen of Rice black-streaked dwarf virus from frozen infected rice leaves to healthy plants of rice and maize. J Phytopathol 2011, 159: 165. 10.1111/j.1439-0434.2010.01742.xView Article
- Wang Q, Zhou GH, Zhang SG: Detection of Southern rice black-streaked dwarf virus using one-step dual RT-PCR. Acta Phytopathol Sin 2012, 42: 84-87. in Chinese
- Zhou T, Du L, Fan Y, Zhou Y: Reverse transcription loop mediated isothermal amplification of RNA for sensitive and rapid detection of southern rice black-streaked dwarf virus. J Virol Methods 2012, 180: 91-95. 10.1016/j.jviromet.2011.12.014PubMedView Article
- Chen Z, Yin C, Liu J, Zeng M, Wang Z, Yu D, Bi L, Jin L, Yang S, Song B: Methodology for antibody preparation and detection of southern rice black-streaked dwarf virus. Arch Virol 2012, . 10.1007/s00705-012-1430-8
- Boonham N, Smith P, Walsh K, Tame J, Morris J, Spence N, Bennison J, Barker I: The detection of Tomato spotted wilt virus (TSWV) in individual thrips using real-time fluorescent RT-PCR (TaqMan). J Virol Methods 2002, 101: 37-48. 10.1016/S0166-0934(01)00418-9PubMedView Article
- Giovanna M, Piero C, Gian P, Emanuela N: Real-time PCR for the quantitation of Tomato yellow leaf curl Sardinia virus in tomato plants and in Bemisia tabaci . J Virol Methods 2008, 147: 282-289. 10.1016/j.jviromet.2007.09.015View Article
- Lopez R, Asensio C, Guzman MM, Boonham N: Development of real-time and conventional RT-PCR assays for the detection of potato yellow vein virus (PYVV). J Virol Methods 2006, 136: 24-29. 10.1016/j.jviromet.2006.03.026PubMedView Article
- Roberts CA, Dietzgen RG, Heelan LA, Maclean DJ: Real-time RT-PCR fluorescent detection of tomato spotted wilt virus. J Virol Methods 2000, 88: 1-8. 10.1016/S0166-0934(00)00156-7PubMedView Article
- Zhang X, Wang X, Zhou G: A one-step real time RT-PCR assay for quantifying rice stripe virus (RSV) in rice and in the small brown planthopper ( Laodelphax striatellus Fallen). J Virol Methods 2008, 151: 181-187. 10.1016/j.jviromet.2008.05.024PubMedView Article
- Zhang X, Zhou G, Wang X: Detection of Wheat dwarf virus (WDV) in wheat and vector leafhopper (Psammotetix striatus L.) by real-time PCR. J Virol Methods 2010, 169: 416-419. 10.1016/j.jviromet.2010.07.029PubMedView Article
- Schmittgen TD, Livak KJ: Analyzing real-time PCR data by the comparative CT method. Nat Protoc 2008, 3: 1101-1108. 10.1038/nprot.2008.73PubMedView Article
- Lee C, Kim J, Shin SG, Hwang S: Absolute and relative QPCR quantification of plasmid copy number in Escherichia coli . J Biotechnol 2006, 123: 273-280. 10.1016/j.jbiotec.2005.11.014PubMedView Article
- Jain M, Nijhawan A, Tyagi AK, Khurana JP: Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem Bioph Res Co 2006, 345: 646-651. 10.1016/j.bbrc.2006.04.140View Article
- Gadiou S, Ripl J, Jaňourová B, Jarošová J, Kundu JK: Real-time PCR assay for the discrimination and quantification of wheat and barley strains of Wheat dwarf virus . Virus Genes 2012, 44: 349-355. 10.1007/s11262-011-0699-0PubMedView Article
- Ruiz–Ruiz S, Ambrós S, Vives MC, Navarro L, Moreno P, Guerri J: Detection and quantitation of Citrus leaf blotch virus by TaqMan real-time RT-PCR. J Virol Methods 2009, 160: 57-62. 10.1016/j.jviromet.2009.04.012PubMedView Article
- Denno RF, Roderick GK: Population biology of planthoppers. Annu Rev Entomol 1990, 35: 489-520. 10.1146/annurev.en.35.010190.002421View Article
- Zhang SX, Li L, Wang XF, Zhou GH: Transmission of Rice stripe virus acquired from frozen infected leaves by the small brown planthopper ( Laodelphax striatellus Fallen). J Virol Methods 2007, 146: 359-362. 10.1016/j.jviromet.2007.05.028PubMedView Article
- Shen JH, Shang JM, Liu GJ: Management of the white-backed planthopper, Sogatella furcifera in China: a mini-review. Chin J Rice Sci 2003,17(S):7-22. in Chinese
- Bao YX, Xu XY, Wang JQ, Wang C, Miu Q, Zhai B: Analysis of the atmospheric dynamical backgrounds for the great immigration events of white backed planthopper ( Sogatella furcifera ). Acta Ecol Sin 2007, 27: 4527-4535. in Chinese
- Wang YK, Zhai BP: Re-migration capacity of the white-backed planthopper, Sogatella furcifera . Acta Entomol Sin 2004, 47: 467-473. In Chinese
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.