Development of a Real-time RT-PCR Method for Rapid Detection and Quantification of Southern Rice Black-streaked Dwarf Virus in Rice

Southern rice black-streaked dwarf virus (SRBSDV), a latest member of the genus Fijivirus within the family Reoviridae, was simultaneously isolated and identified from the rice in southern of China in 2008 [1,2]. In the following three years (2009-2010), SRBSDV caused the most important rice disease in South of China, there were over ten millions hectare of rice infected, and resulted in massive devastation of rice yield [3].

Co., Ltd, China). The purity was tested by the ratio of OD 260 /OD 280 absorbance, and RNA concentration was measured at OD 260 on a spectrophotometer and calculated (Tu-1901, China). Constant amounts of 1 µg of RNA were reversely transcribed to cDNA using Primescript II 1st Strand cDNA Synthesis Kit with random 6 mers primer according to manufacture's introduction (Takara, Bio Inc, China), cDNA synthesis condition: 25°C for 10 min, followed by 42°C for 30 min, 85°C for 5 min, and then stored at -20°C.

Primers design
The nucleotide sequences of segment 9 of SRBSDV and RBSDV were downloaded for the GenBank database, and there was high homology of genome sequence between SRBSDV with RSBDV (74.2~74.9% identity of segment 9) [2]. Sequence multi-alignment was analyzed by software suite of DNAMAN (Lynnon Biosoft Inc, USA). Primers in the low homology regions segment 9 of SRBSDV were designed in comparison with RBSDV ( Figure 1) and by using nucleotide sequence of segment 9 of SRBSDV (EU784843) as target template sequence. Primers, which are specific to SRBSDV, were designed using DNASTAR software (DNASTAR, Inc, USA), and comparison analysis was performed with the sequence in the GenBank nucleotide database by nucleotide BLAST (http://www.ncbi.nlm.nih.nog/).

Recombinant plasmid preparation
The target fragments of Segment 9 of SRBSDV genome were amplified by the designed primers (Table 2) in 20 µl volume solution, which consisted of 2 µl of the above cDNA, 2.5 µl of PCR Buffer, 0.5 µl of dNTP (10 mmol/l), 1.5 µl of each primer (10 µmol/l), 0.5 µl of Taq DNA polymerase (5U/l) (Takara Bio Inc, China) and 13 µl of sterilized water. PCR reaction was carried out under the following conditions: 94°C for 5 min, followed by 35 cycles at 94°C for 30 s, 58°C for 30 s, 70°C for 30 s, and a final extension at 70°C for 10 min. The PCR products were analyzed by 1.5% agarose gel electrophoresis.
Ten PCR reactions were conducted for eliminating artifacts with controls (no cDNA). The target PCR products were cut from the agrose gel and recycled by a commercial kit (TIANgel Midi Purification Kit, Tiangen Biotech (Beijing) Co., Ltd, China) according to manufacturer's guidelines.
The plasmid was constructed by inserting the PCR product into the pGEM-T Easy Vector (Promega) according to kit introduction, and then the recombinant was transformed into competent E. coli JM109 cells. The cells containing recombinant plasmid were selected by ampicillin (50 mg/L) and verified by PCR and sequence. The recombinant plasmid DNA was extracted using TIANprep Mini Plasmid Kit (Tiangen Biotech (Beijing), Co., Ltd, China).

Real-time RT-PCR
The recombinant plasmid was quantified by absorbance at OD 260 nm on a spectrophotometer (Tu-1901, China) and the copy numbers were calculated according to the formula [9]. Copies/ µl=6×10 23 copies/ mol×(C/MW) (C: plasmid concentration [measured by ultraviolet spectrophotometer at 260 nm], MW: molecular weight, g/mol). PCR was performed according to the manufacturer's instruction (TransStart TM Green qPCR SuperMix UDG, Transgen Biotech Co., Ltd, China). The real-time PCR reaction conditions were as follows: 50°C for 2 min, 95°C for 10 min, 35 cycles of 95°C for 15 s, 58°C for 30 s, and 72°C for 30 s, with a CFX96 Thermal cycler (Bio-Red, USA). The 25 µl real-time PCR mixture contained 1 µl cDNA as template (gradient dilution to proper copies of recombinant plasmid), 0.5 µl each sense and anti-sense primer (to a final concentration at 0.2 µM), 12.5 µl 2×Transstart Green qPCR SuperMix UDG, 10.5 µl ddH 2 O. For each experiment, negative control was simultaneously performed by a non-template reaction in triplicate. The specificity of the real-time PCR was confirmed by amplicons size in 1% (W/V) agarose gel.
Threshold cycle (Ct) values were determined at the fluorescence threshold line and arithmetic mean of the triplicate values was calculated. Samples were considered positive only if Ct value was <35 for all replicates [13].

Determination of sensitivity and reproducibility of real-time RT-PCR
Serially gradient positive plasmids (4.04×10 2 -4.04×10 7 copies/µl) were used as templates to determine the sensitivity of the real-time PCR. Intra-assay variability was tested by running a single real-time PCR using four different series in triplicate. Inter-assay variability was determined by running two separate real-time PCR by each dilution

Reproducibility of real-time RT-PCR
The reproducibility of this method was tested using four dilution series of standard plasmids. As shown in table 1, the intra-assay of this method (mean ± S.D of the CV) was 2.86 ± 0.40% (variation range: 1.96-3.59%), and the inter-assay of this method (mean ± S. D of the CV) was 3.51 ± 0.37% (variation range: 2.90-4.37%). The results demonstrated excellent reproducibility of this method.

Testing of field samples
Some of rice leaf samples (with or without symptoms) from each of four districts were tested by the real-time RT-PCR, compared with conventional RT-PCR. The positive rate by the real-time RT-PCR was 87.5%-100%, which was higher than conventional RT-PCR (63.6%-100%) ( Table 2).

Discussion
Although, SRBSDV is the latest number of the genus Fijivirus within the family Reoviridae, the infected rice by this virus blossomed in southeast of Asia [3,16]. For diagnosis of SRBSDV, typical symptoms and RT-PCR methods need to be detected, and these two methodological approaches are likely to complement rather than replace each other [5]. To best of our knowledge, there are no publications of using the direct molecular quantitative detection of SRBSDV. In this study, the real-time RT-PCR method for quantitative detection of SRBSDV has demonstrated to be specific and sensitive for detection of field rice samples.
The real-time RT-PCR for SRBSDV was designed and used in the field rice samples based on the low homology regions of segment 9 of RBSDV. The results of this study confirmed the specificity of this method for detecting SRBSDV, since the target of amplification was only homology to SRBSDV by the nblast for optimizing the primers ( Figure  S2). This method was also sensitivity, because of its ability of detection at low density of 150 copies in one reaction. The reproducibility of this method was tested by four dilution series of standard plasmids, and the excellent reproducibility was verified by CV below 4.5%. On the basis of recombinant plasmid standard and not the total RNA standard, the real-time RT-PCR contributed to long-term storage and operation, because plasmid did not easily degraded [9].
Conventional serological methods were efficient and specific for detecting rice viruses, such as RBSDV [17]. At the time of this study, in triplicate. Statistical analysis was performed using DPS software (version 12.1) [14], and the mean value, Standard Deviation (SD) and Co-efficient Of Variation (CV) were used to evaluate the reproducibility of the real-time PCR.

Specificity of real-time RT-PCR
The specificity of primers of real-time RT-PCR was assessed using nucleotide BLAST (http://ncbi.nlm.nih.gov/), and both primers had no significant homology for other sequences of genus Fujivirus group 2, including the highest homology species of RBSDV. In order to verify the specificity of primers between SRBSDV and RBSDV, conventional RT-PCR was performed in duplicate and electrophoresis in agarose gel ( Figure S1). PCR by both specific primers have expected target and distinct specified band from SRBSDV infected rice sample, however no from RBSDV infected rice sample. The band was purified and sequenced, the each sequence was highly homology to SRBSDV using nucleotide BLAST ( Figure S2).
The conventional RT-PCR result ( Figure S2) also showed that the amplification efficiency by primer S9TF/S9TR was higher than that by primer S9RF/S9RR. The primer S9TF/S9TR was selected for further real-time RT-PCR experiment.

Standard curve and sensitivity of real-time RT-PCR
Standard curve was generated by 10-fold serial dilutions of recombinant plasmid (4.04×10 2 -4.04×10 7 copies/ µl) (Figure 2), and a strong linear relationship between the Ct and the log of the copy number was verified (R 2 ≥ 0.971). The slope of standard curve was -3.901, and the efficiency of the reaction calculated by 10 (-1/slope) was 1.80, which was considered acceptable, as it ranged between 1.7-2.3 [15]. The linear equation for the real-time RT-PCR was y=-3.901x+6.068, this method   This real-time RT-PCR assay is more precise and sensitive than symptoms and RT-PCR method. Some of field rice samples with suspected symptoms were not infected with SRBSDV, which was confirmed by real-time RT-PCR and conventional RT-PCR. The positive rates (87.5%-100%) of field rice samples infected with SRBSDV using real-time RT-PCR was higher than those (63.6%-100%) of the conventional RT-PCR. The real-time RT-PCR is known of high accuracy for detecting other viruses [19], and this study also demonstrated that real-time RT-PCR was more sensitive as compared to the conventional RT-PCR.
When we prepared the draft of this work, similar quantitative detection of SRBSDV and RBSDV by TaqMan was published [20]. Quantification methods by TaqMan and SYBR Green are reliable for determining gene expression, and although lower sensitive than TaqMan, SYBR Green has its merits of ease in designing the assays and relatively low setup and running costs [21]. So both methods should be rather alternative according to requirements of experiment than substitutive each other.
In summary, the real-time RT-PCR was able to detect SRBSDV, and this might also be important for standardization of quantified detection of SRBSDV. Furthermore, it could potentially be applied for monitoring the virus in the field, predicting virus epidemic development and studying virus-plant-vector interactions [20].