IMPROVED DETECTION OF ILARVIRUSES AND ... - SIPaV

Journal of Plant Pathology (2014), 96 (3), 577-583

Edizioni ETS Pisa, 2014

Osman et al.

577

Short Communication

IMPROVED DETECTION OF ILARVIRUSES AND NEPOVIRUSES AFFECTING FRUIT TREES USING QUANTITATIVE RT-qPCR F. Osman, M. Al Rwahnih and A. Rowhani Department of Plant Pathology, University of California, Davis, CA 95616, USA

Running title: qPCR detection of Ilarviruses and Nepoviruses in fruit trees SUMMARY

Reverse transcription quantitative PCR (RT-qPCR) assays were developed for the detection of the ilarviruses Prunus necrotic ringspot virus (PNRSV), Prune dwarf virus (PDV), Apple mosaic virus (ApMV), and American plum line pattern virus (APLPV), and the nepoviruses Tomato ringspot virus (ToRSV) and Cherry leafroll virus (CLRV). These viruses affect various stone fruits such as apricots, cherries, peaches, plums, and almonds. The goal of this work was to improve the RT-qPCR detection of PNRSV, PDV, and ApMV in addition to developing three new RT-qPCR assays for the detection of APLPV, ToRSV and CLRV. Primers for conventional RT-PCR as well as primers and probes for RT-qPCR assays were designed after aligning coat protein (CP) gene sequences of geographically diverse isolates with the corresponding CP gene sequences from the GenBank, targeting regions with 100% sequence identity. The efficiency of each RT-qPCR assay, as well as the intra- and inter-assay variability were determined. These conventional RT-PCR and RT-qPCR assays were validated using purified total RNAs from 221 trees from the USDA Clonal Germplasm Repository orchards. The data showed that more isolates were detected by RTqPCR than by RT-PCR. Key words: Ilarviruses, Nepoviruses, RT-qPCR, RT-PCR

Prunus necrotic ringspot virus (PNRSV), Prune dwarf virus (PDV), Apple mosaic virus (ApMV), and American plum line pattern virus (APLPV) are members of the genus Ilarvirus. Among these viruses, PNRSV and PDV are the most economically important (Nemeth, 1986; Howell and Mink, 1988; Hadidi et al., 2011). PNRSV can cause serious damages including reduced bud take in the nurseries, reduced growth and vigor of infected trees, yield losses, delayed fruit maturity, reduced fruit quality and increased susceptibility to cold and winter injury in the orchards (Hadidi Corresponding author: A. Rowhani Fax: +1.530.752.2132 E-mail: [email protected]

et al., 2011; Németh, 1986). PDV substantially reduces bud take in the nurseries, causing significant yield reduction especially in almond, peach and sweet cherry (Hadidi et al., 2011). Cherry leafroll virus (CLRV) and Tomato ringspot virus (ToRSV) are members of the genus Nepovirus. CLRV affects different species of perennial plants including stone fruit and nut trees. ToRSV affects grapevines and different fruit tree species (Mayo and Robinson, 1996). ToRSV may cause serious diseases in some of the perennial crops such as apple union necrosis and decline (Ramsdell, 1995), prunus stem pitting (Civerolo and Mircetich, 1972), peach yellow bud mosaic (Cadman and Lister, 1961) and red raspberry decline (Stace-Smith, 1984). Diseases caused by ToRSV are severe in trees that become infected at an early stage of development, with mortalities of 40-90% reported in infected orchards (Stouffer and Uyemoto, 1976). Detection of ilarviruses is affected by the uneven distribution of virus particles within infected trees (Torrance and Dolby, 1984) and fluctuation of the titer between seasons (Dal Zotto and Nome, 1999). Similarly, detection of nepoviruses in fruit trees is often compromised by the low concentration of the viruses in plant tissues (Polak et al., 2004). Biological indexing can be used to detect ilarviruses (Bertozzi et al., 2002) and nepoviruses (Polak et al., 2004), but this detection method is labor intensive and requires several months to few years for symptom development (Nienhaus and Castello, 1989). Serological methods, such as ELISA, are often used to detect these viruses (Torrance and Dolby, 1984; Mekuria et al., 2003; Rowhani et al., 1985), but this assay is not sensitive enough especially if used late in the growing season when the viruses are present in low concentration (Uyemoto et al., 1989; Spiegel et al., 1996). Several other methods have been developed for the detection of these groups of viruses including the use of a unique polyprobe (poly 10) carrying partial sequences of different plant viruses or viroids fused in tandem, which has permitted the simultaneous detection of eight viruses using a non-radioactive molecular hybridization procedure (Peiró et al., 2012). More recently, RT-PCR, either on its own or in combination with serological methods showed a practical alternative to previous methods, due to its high specificity and sensitivity for the detection of ilarviruses (Rowhani et al., 1998; Helguera et al., 2001; Osman et al., 2012a) and nepoviruses (Rowhani et al., 1998; Kumari, 2009; Osman

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qPCR detection of ilarviruses and nepoviruses in fruit trees

Journal of Plant Pathology (2014), 96 (3), 577-583

Table 1. Sequences of RT-PCR primers and qPCR assays used for the detection of Prunus necrotic ringspot virus (PNRSV), Prune dwarf virus (PDV), Apple mosaic virus (ApMV), American plum line pattern virus (APLPV), Tomato ringspot virus (ToRSV) and Cherry leafroll virus (CLRV). All the PCR primers for these viruses Tablewere 1 designed from the coat protein (CP) gene.

Sequences of RT-PCR primersAssay/Target and qPCR assays used for the detection of Prunus necrotic ringspot ilarvirus (PNRSV), Prune dwarf Product 1 Virusilarvirus Primer Primer Sequence Location Reference (PDV), Apple mosaicgene+Probe ilarvirus ( ApMV), American plum line pattern ilarvirus (APLPV), Tomato ringspot nepovirus size (bp) (ToRSV) and Cherry leafroll type nepovirus (CLRV). All the PCR primers for these viruses were designed from the coat protein (CP) gene. PDV V2

PDV

PDV C

Virus PNRSV

PNRSV 1805 R

PDV APLPV

Primer

PNRSV 1425 F

PDV V2

APLPV 1493 PDV CF

RT-PCR, CP Assay/Target

TORSV-62 F CLRV-1721 R ToRSV TORSV-738 18S rRNA 449 f R 18 S CLRV-1385 18S rRNA 498 r F rRNA CLRV CLRV-1721 R 18S rRNA 475 p

TAGTGCAGGTTAACCAAAAGGAT

gene+Probe Primer Sequence GACTTCACGACCACTCTCCCTC type RT-PCR, CP

CTAGATCTCAAGCAGGTCTTCATCG CCGGTATGATATCTCGTACCGAG

RT-PCR, CP GGTCGTCAAGGGAGAGGC TAGTGCAGGTTAACCAAAAGGAT RT-PCR, CP TCATCAGGGACTAGTAAATTTGCG GACTTCACGACCACTCTCCCTC

APLPV-1906 PNRSV R1425 F PNRSV ApMV CP sense RT-PCR, CP PNRSV 1805 R ApMV RT-PCR, CP ApMV CP antisense APLPV 1493 F APLPV RT-PCR, CP TORSV-62 F APLPV-1906 R ToRSV RT-PCR, CP TORSV-738 ApMV RCP sense ApMV RT-PCR, CP ApMVFCP antisense CLRV-1385

CLRV

CCGGTATGATATCTCGTACCGAG

RT-PCR, CP

CTGAGAGGAGGACAGCTTGG CTAGATCTCAAGCAGGTCTTCATCG

CCGGTGGTAACTCACTCGTT GGTCGTCAAGGGAGAGGC TCATCAGGGACTAGTAAATTTGCG ACGCCAAGGGTGGAACTTT CTGAGAGGAGGACAGCTTGG CCCATGTAAAGTGCCATTCG CCGGTGGTAACTCACTCGTT GACCGTGTAACGGCAACAGT

ACGCCAAGGGTGGAACTTT TGAGTCCGACACTCATACAATAAGC RT-PCR, CP CCCATGTAAAGTGCCATTCG GTGACGGAGAATTAGGGTTCGA RT-qPCR assay GACCGTGTAACGGCAACAGT FAM- TAMRA CTGCCTTCCTTGGATGTGGTA TGAGTCCGACACTCATACAATAAGC RT-PCR, CP probe CCGGAGAGGGAGCCTGAGAAACGG

1404-1427

622 Product size 2026-2003 1

Osman et al., 2012

380

Osman et al., 2012

1425-1446 (bp)

1805-1781 1404-1427

1493-1511 2026-2003

1909-1886 1425-1446 236-255 1805-1781

236-255 4699-4679 687-667 1385-1405

431

4022-4041 1722-1697 4699-4679

677

1385-1405

426-406

1722-1697

CP-340p1 PDVPDV   PDV CP-285f1 PNRSV CP-319f PDV CP-285f2 PDV CP-412r PNRSV PNRSV CP-469r PDV CP-340p1  PNRSV CP-363p PNRSV PNRSV APLPV-1518f CP-319f PNRSV CP-469r APLPV APLPV-1600r PNRSV CP-363p APLPV-1554p APLPV-1518f APLPV ApMV-111f1 APLPV-1600r ApMV-111f2 APLPV-1554p

1560-1579 1504-1526

ApMVApMV ApMV-312r1 ApMV-111f1 ApMV-312r2 ApMV-111f2

UPL ApMV-312r1 #101

ApMV-312r2 TOgen-210fg UPL #101 TOgen-210ff

TGAACTTCCTACGTTGTAGGGGATT TCTAYGGACTCATTAAAGGT TGATACCAAGGTRTACGGAATTG

GAGGAGGA CCAGTGAAGTTGGCAAGTTTATTG

69

1631-1607

RT-qPCR assay TGATACCAAGGTRTACGGAATYG 1504-1526 CCKCAGTTGATGGGTCAGAATTT 1443-1465 RT-qPCR assay CP gene-MWG TGAACTTCCTACGTTGTAGGGGATT 1631-1607 CP gene-FAM CCTTCAAGAACCCCTTCCTAGAC 1593-1571 probe 1560-1579 TCTAYGGACTCATTAAAGGT TAMRA probe CCGAATGAACTCTATGAGTTCGAATGGTTGG 1487-1518 CCKCAGTTGATGGGTCAGAATTT 1443-1465 RT-qPCR assay TCGACGACCGCTGGTCA 1521-1537 RT-qPCR assay 1593-1571 CP gene-FAM CCTTCAAGAACCCCTTCCTAGAC CP gene-MWG GAGTTCAATTGAACTCCCATCTCG 1603-1580 TAMRA probe CCGAATGAACTCTATGAGTTCGAATGGTTGG 1487-1518 probe AGTACTTACCTCGAGAAAT 1557-1575 1521-1537 RT-qPCR assay TCGACGACCGCTGGTCA AAGCGAACCCGAATAAGGGT 175-194 1603-1580 CP gene-MWG GAGTTCAATTGAACTCCCATCTCG AGCGAACCCGAACAAGGG 176-193 AGTACTTACCTCGAGAAAT 1557-1575 RT-qPCRprobe assay CP gene-UPL CGGAAGACATCGGCAAAGTC 378-359 AAGCGAACCCGAATAAGGGT 175-194 probe CACGAAGACATCGGCAAAGTC 379-359 AGCGAACCCGAACAAGGG 176-193 RT-qPCR assay CGGAAGACATCGGCAAAGTC 378-359 240-247 CP gene-UPL GAGGAGGA CACGAAGACATCGGCAAAGTC 379-359 probe CCAGTGACGTTGGCTAATTTATTG 4240-4264

RT-qPCR assay

335

381-405

357-389 1504-1526 426-406 1504-1526 381-405

probe

388

380 388

357-389

Osman et al., 2012 Osman et

622

687-667 1493-1511 1909-1886 4022-4041

GTGACGGAGAATTAGGGTTCGA 18 SPDV 18S rRNA 449 f CP-285f1 RT-qPCR assay TGATACCAAGGTRTACGGAATTG CTGCCTTCCTTGGATGTGGTA rRNA 18S rRNA 498 r RT-qPCR assayFAM-TGATACCAAGGTRTACGGAATYG 18S rRNA) PDV CP-285f2 CCGGAGAGGGAGCCTGAGAAACGG 18S rRNA 475 p CP gene-MWG PDV  TAMRA probe

PDV CP-412r

Reference

Location

127

al., 2012

Osman et Hassan et 431al., 2012 Osmanal., et 2006 al., 2012 Osman et 677 Hassanal., et2012 al., 2006 Osman et 335 Osmanal., et 2012 al., 2012 Osman et 69Osman et al., 2007 al., 2012 Osman et

127al., 2007 This study

This study

150

This study

 

150 82This study This study 82

This study 204

204

This study

This study

240-247

4240-4264

CCAGTGACGTTGGCTAATTTATTG 4240-4264 TOgen-210fg ToRSVToRSV TOgen-391rg CP gene-MWG GCTTCCGCAGGAACATCATT 4423-4402 183 This study CCAGTGAAGTTGGCAAGTTTATTG 4240-4264 TOgen-210ff RT-qPCR assay probe TOgen-391rf CTGCTTCTGCAGGAACATCATT 4421-4402 4423-4402 TOgen-391rg 183 This study CP gene-MWG GCTTCCGCAGGAACATCATT TOgen-273p ACGTGGACGTTTGATAT 4303-4319 CTGCTTCTGCAGGAACATCATT 4421-4402 TOgen-391rf probe ACGTGGACGTTTGATAT 4303-4319 CLRV-1f TGGCGACCGTGTAACGG 1381-1397 TOgen-273p TGGCGACCGTGTAACGG 1381-1397 CLRV-1f CLRV-83r1 TACTACTAAGACCGGTCGCATGG 1463-1441 CLRV RT-qPCR assay TACTACTAAGACCGGTCGCATGG 1463-1441 CLRV-83r1 RT-qPCR assay TACTACTAAGACCGGTCGCATGAA CLRV CLRV-83r2 CP gene-MWG 1463-1440 82 This study 1463-1440 CP gene-MWG TACTACTAAGACCGGTCGCATGAA CLRV-83r2 82 This study probe CLRV-17p1 GTTAAGGTGACACTGGTGG 1405-1423 probe GTTAAGGTGACACTGGTGG 1405-1423 CLRV-17p1 CLRV-17p2 TTACGGTGACACTGGTGG 1406-1423 TTACGGTGACACTGGTGG 1406-1423 CLRV-17p2 Forward primers: F, f, sense Reverse primers: R, r, antisense qPCR probe: P - Y=: C or T, K= G or T. UPL probe: Universal Probe library "Roche" MWG probe: Minor Groove binding probe (AB) FAM- TAMRA probe: 5' FAM-3' TAMRA dual labelled probe 18 S rRNA is based on accession no. L28749, PNRSV on U57046, PDV on L28145, APLPV on nc_003453, AMV AY0543853, ToRSV on D 12477 and CLRV on Z 34265

et al., 2012a). One-step multiplex RT-PCR methods were also used for the diagnosis of PNRSV, PDV, Plum pox virus (PPV) (Jarosova and Kundu, 2010), PNRSV, PDV, ApMV,

APLPV (Sanchez-Navarro et al., 2005), PNRSV, PDV, and ApMV (Saade et al., 2000); and another pentaplex RT-PCR was adopted for the detection of ApMV together

Journal of Plant Pathology (2014), 96 (3), 577-583

with Apple stem pitting virus (ASPV), Apple chlorotic leaf spot virus (ACLSV), and Apple stem grooving virus (ASGV) (Menzel et al., 2003; Hassan et al., 2006). In the last decade new advancements in quantitative PCR (qPCR) have made significant improvements in methods used to detect tree pathogens (Salmon et al., 2002; Marbot et al., 2003; Schneider et al., 2004; Olmos et al., 2005; Roussel et al., 2005; Varga and James, 2005). The objective of this work was to improve the reliability of RTqPCR method used for the detection of PNRSV, PDV, and ApMV and to develop and evaluate three new RT-qPCR assays for the detection of APLPV, ToRSV and CLRV. To provide samples for designing the RT-qPCR assays as well as testing both RT-PCR and RT-qPCR, samples from 221 orchard trees originating from various geographical regions around the world and from different species of fruit trees (Osman et al., 2012a) were acquired from the USDA National Clonal Germplasm Repository (NCGR) collection in the spring. Composite samples consisted of eight petioles (including base of the leaves) randomly collected from various locations of the trees and combined. Trees sampled included 63 peach (Prunus persica L.), 45 apricot (P. armeniaca L., P. mume and P. manddhurica), 43 cherry (P. avium L., P. cerasus L., P. tomentosa, P. mahaled, P. pseudocerasus, P. virginiana and P. serotina), 47 plum (Prunus domestica L., P. salicina L., P. bokhariensis L., and P. munsoniana), and 23 almond (P. bucharia, P. dulcis, P. triloba, P petunnikowii and P. pedunculata). All virus isolates used as positive controls were maintained in Prunus species grown in the field except for ApMV which was maintained in roses. These samples were homogenized as previously described (Osman et al., 2012b). Eight hundred microliters of the aqueous phase was subjected to RNA extraction using the MagMaxTM Express-96 (Applied Biosystems, USA) with the MagMaxTM 96 Viral RNA isolation kit (Life Technologies, USA) as per manufacturer’s instructions. Total RNA was eluted in 100 µl DEPC-treated water. The integrity of total RNA was analyzed by RT-qPCR using the 18S rRNA as housekeeping gene, as described by Osman et al. (2007). To improve the reliability of RT-PCR detection as well as to develop RT-qPCR assays, sequences of the CP gene from a large number of samples for the viruses under investigation were generated. RT-PCR amplification was performed to screen 221 samples from the trees in the NCGR collection using primers listed in Osman et al. (2012a). The tested trees included those infected with PNRSV (55 trees), PDV (19 trees), APLPV (4 trees), and CLRV (1 tree) (Osman et al., 2012a). RT-PCR reactions were prepared according to Osman et al. (2012b). RT-PCR products of the CP gene region for all viruses were eluted from the gels using the ZymoClean Gel DNA Recovery Kit (Zymo Research, USA) and sequenced from both directions. The generated sequences for each virus were aligned with the corresponding CP gene sequences available in GenBank using Sequence Analysis and Molecular Biology

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Data Management software Vector NTI Advance™ 11.5 (Invitrogen, USA). Sequences were subjected to BLAST analysis (Altschul et al., 1997), then the aligned CP gene sequences for each virus were used to design both conventional RT-PCR primers as well as RT-qPCR primers and probes using the AB Primer Express™ software (Invitrogen, Life Technologies, USA). The corresponding GenBank CP gene sequences used included: 243, 102, 76, 13, 7, and 37 for PNRSV, PDV, ApMV, APLPV, CLRV, and ToRSV, respectively. For RT-PCR, the primers and protocols were as described previously (Osman et al., 2012a), except for the ApMV primers which were designed by Hassan et al. (2006; Table 1). For RT-qPCR assay, the primers and probes for the specific detection of the viruses were designed from the CP gene sequence pile up as listed in Table 1. The design of primers and probes for RT-qPCR assays was carried out under specific criteria set by the AB Primer Express™ software (Invitrogen, Life Technologies, USA). Previous tests with primers design had shown that using more than one primer in the reaction mix works better than including degenerate nucleotide in the primer or probe sequence except for PDV and PNRSV. Therefore, more than one forward or reverse primer was designed for PDV, ApMV, ToRSV and CLRV and two qPCR probes for CLRV (Table 1) to include all sequence variations between different isolates. Different RT-qPCR probes were used for each virus as listed in Table 1. The one-step RT-qPCR reactions using the AgPathIDTM One-Step RT-PCR Kit (Life Technologies, USA) as well as the amplification protocols were as described by Osman et al. (2012b). The data were quantitatively analyzed both by measuring the quantitative cycles (Cq) in a Microsoft Excel program and graphically by an amplification plot. Cq values were exported with a threshold of 0.04 and a baseline of 3-10 for all pathogens and a threshold of 0.1 and a baseline of 2-5 for the 18S rRNA assay. A Cq value below 40 indicated a positive result and a value of 40 indicated no amplification or a negative result. Positive and negative controls were run for each assay. The standard curves for each virus was assessed by using RNA samples that were previously confirmed by RTqPCR designed for each individual virus, with Cq values ranging from 18-20 (indicating a high viral copy number). A dilution endpoint analysis was performed using undiluted total RNA and tenfold dilutions of up to 1:106 of three different samples, each in triplicate. Standard curves were plotted for the quantification cycle (Cq) value of each set of serial dilutions against the logarithm of the concentration for the exponential phase of the reaction and fitting a straight line to these data by simple linear regression (Bustin et al., 2009). The amplification efficiency (E) of all assays was determined from the slope of a standard curve generated on a 10-fold dilution in triplicate for every RNA sample using the formula E = 10 –1/slope – 1. Optimal qPCR efficiency was achieved at a slope of –3.32 (Bustin

Journal of Plant Pathology (2014), 96 (3), 577-583

qPCR detection of ilarviruses and nepoviruses in fruit trees

Cq Value

580

y = -3.577x + 37.23 R² = 0.999 E=90.3

Cq Value

0

1

2

40 35 30 25 20 15 10 5 0

4

5

y = -3.427x + 39.89 R² = 0.982 E=93.4

0

6

1

2

40

ApMV

3

4

5

6

ApLPV

35 30 25 20 15

y = -3.286x + 38.08 R² = 0.996 E=100.9

y = -3.539x + 40.33 R² = 0.998 E=91.7

10 5 0

0

1

2

3

4

5

6

ToRSV

40 35 Cq Value

3

PNRSV

40 35 30 25 20 15 10 5 0

PDV

40 35 30 25 20 15 10 5 0

1

2

3

35

30

30

25

25

4

5

6

7

CLRV

40

20

20

y = -3.382x + 43.32 R² = 0.996 E=97.6

15 10 5

y = -3.412x + 41.06 R² = 0.998 E=96.5

15 10 5 0

0 0

1

2

3

Dilutions

4

5

6

0

1

2

3

4

5

6

Dilutions

Fig. 1. Standard curve analysis of quantitative polymerase chain reaction (qPCR) sensitivity. The x-axis represents the logarithm 1. Standard curve analysis of represents quantitative chain reaction The x-axis of the Fig. diluted RNA quantity and the y-axis thepolymerase measured quantification cycle(qPCR)sensitivity. (Cq) value.

represents the logarithm of the diluted RNA quantity and the y-axis represents the measured quantification cycle (Cq) value. et al., 2009). The determination coefficient (R 2) was also 0.63% to 1.682% and 0.95% to 1.89%, respectively. For calculated to determine the validity of the linear regresAPLPV it was in the range of 0.230% to 1.120% and 0.09 sion. All experiments were duplicated. The efficiency of to 1.31%, respectively. For ToRSV the CV% of the intraall RT-qPCR assays is shown in Fig. 1. assay and inter-assay variation were in the range of 0.321% The intra- and inter-assay variation, which is the ability to 1.054% and 0.95% to 1.89%, respectively. For CLRV of the assay to produce consistent results when sub-samthe CV% of the intra-assay and inter-assay variations were ples are taken from the same plant material source (i.e. re0.38% to 1.36% 0.65% to 1.27%, respectively. peatability), was calculated by determining the percentage RT-PCR and RT-qPCR designed from the same seof coefficient of variation (CV%) in the same plate (interquence alignments of each virus were used to confirm the assay) and two different plates (intra-assay). To obtain the infection status of the 221 randomly selected fruit trees intra- and inter-assay precisions, total RNAs from three listed above. Uninfected trees as well as trees infected with different samples for each virus were extracted. Tenfold PNRSV, PDV, ApMV, APLPV, ToRSV and CLRV were serial dilution were prepared for each and tested by qPused as control. CR in triplicate and their Cq values were calculated. The A comparative analysis of RT-PCR and RT-qPCR outCV% was calculated for each sample as follows: mean of puts using 221 trees of different species and cultivars the standard deviations of the duplicates divided by the showed that RT-qPCR was more sensitive and reliable grand mean of the duplicates ×100. For PDV, the CV% of than RT-PCR, and detected more infected trees (Fig. the intra-assay and inter-assay variation were in the range 2). In order to prevent serious losses to the stone fruit of 0.103% to 1.917% and 0.65 % to 2.4%, respectively. industry, effective control measures of ilarviruses and For PNRSV, the CV% of the intra-assay and inter-assay nepoviruses are needed. The best control measure will variation were in the range of 0.272% to 1.666% and include the use of virus-tested planting stocks for propa1.05% to 2.31%, respectively. For ApMV the CV% of the gation. Molecular assays have proven to be invaluable in intra-assay and inter-assay variation were in the range of the rapid detection and identification of these viruses.

Journal of Plant Pathology (2014), 96 (3), 577-583

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70 60

% of infected varieties

50 40 30 20 10

PDV

PNRSV

APLPV

RT-qPCR

RT-PCR

RT-qPCR

RT-PCR

RT-qPCR

RT-PCR

RT-qPCR

RT-PCR

RT-PCR

RT-qPCR

0

ToRSV

CLRV

Viruses

PDV

PNRSV

APLPV

ToRSV

CLRV

RT-PCR RT-qPCR RT-PCR RT-qPCR RT-PCR RT-qPCR RT-PCR RT-qPCR RT-PCR # of infected samples

% of infection

RT-qPCR

19

23

55

146

4

17

0

11

1

27

8.60%

10.41%

24.66%

66.06%

1.79%

7.69%

0%

4.98%

0.455%

12.22%

Fig. 2. Comparison Fig.2. between RT-PCR between and RT-qPCR inand detecting PDV, PNRSV, PDV, APLPV, ToRSV and CLRV in 223 Fruit trees vaComparison RT-PCR RT-qPCR in detecting PNRSV, APLPV, rieties. ToRSV and CLRV in 223 Fruit trees varities.

RT-PCR and multiplex RT-PCR have been developed for detection of viruses in fruit trees (Jarosova and Kundu, 2010; Sanchez-Navarro et al., 2005). However, these techniques have some limitations which include the inability to detect viruses present in samples at low titer, problems with primer dimer formation and post amplification gel documentation. In this report a comparative analysis of RT-PCR and RT-qPCR outputs using 221 trees of different species and cultivars, showed that RT-qPCR was more sensitive and reliable than RT-PCR and could detect more infected trees (Fig. 2). This RT-qPCR detection could be used for routine testing and screening of fruit tree material for these viruses. While the detection of pathogens by RT-qPCR is becoming simpler, there are still major challenges related to the lack of GenBank sequence information from which specific RT-qPCR assays can be designed. In accordance with other authors (Marbot et al., 2003; Roussel et al., 2005), efficient diagnostic RT-qPCR assay should be designed from a large number of sequence alignments of the target gene from many different infected trees derived

from wide geographical regions and corresponding GenBank sequences. Early reports of RT-qPCR detection of PNRSV, PDV and ApMV have indicated that RT-qPCR performance was similar to RT-PCR (Marbot et al., 2003), or failed to detect these viruses (Roussel et al., 2005). The possible reasons for this failure are related to the design of robust assays from limited sequence information available in GenBank (Marbot et al., 2003; Roussel et al., 2005), and the increased length of the RT-qPCR amplicon (Marbot et al., 2003). Increasing the length of RT-qPCR amplicon would increase the risk of reaching saturation level of fluorescence or of depleting the PCR reagents too rapidly (Bustin et al., 2009). Roussel et al. (2005) also reported that RT-qPCR designed for PDV and ApMV failed to detect all virus isolates with a single specific probe, designed from very few published PDV sequences in the GenBank. This was due to the presence of a single nucleotide difference between the designed probe and the corresponding target sequence, preventing the florescence detection in the qPCR assay. However, in this study we developed more sensitive assays for this virus using MGB probes designed

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from multiple CP sequence alignment in highly conserved genomic regions. We demonstrated here the importance of choosing adequate primers and probes for use in RT-qPCR analysis which were designed from a large number of sequences generated in this study and those available in the GenBank. Comparative results of RT-qPCR and RT-PCR detection showed that all the newly designed RT-qPCR assays were able to detect more virus isolates than conventional RT-PCR. For example, the PNRSV RT-qPCR assay was able to detect 146 (66%) isolates while RT-PCR primers designed from the same PNRSV pile up sequences detected 55 (24.7%) and similar results were obtained for other viruses used in this study (Fig. 2). The PDV RTqPCR detected 23 (10.1%) isolates compare to 19 (8.6%) by RT-PCR. The APLPV RT-qPCR detected 17 (7.69%) isolates compare to 4 (1.79%) by RT-PCR. The ToRSV RTqPCR detected 11 (4.98%) isolates compare to 0 (0%) by RT-PCR and finally CLRV RT-qPCR detected 27 (12.2%) isolates compare to 1 (0.455%) by RT-PCR. However, no ApMV infected tree was detected in the collection using either ApMV RT-qPCR or RT-PCR assays. In conclusion, the high sensitivity of the designed RTqPCR assays reported here for the detection of PNRSV, PDV, ApMV, APLPV, ToRSV and CLRV makes it possible to detect and quantify early infections of fruit trees with some of these viruses, as in the case of PNRSV where low levels of virus titer have been reported in dormant woods in the winter (Spiegel et al., 1996). RT-qPCR detection should be considered as the method of choice for routine diagnosis of these viruses, specifically incorporating this method into testing protocols during post-entry quarantines for rapid initial screening of imported budwood. These RT-qPCR assays can also be useful for large-scale applications where sensitivity, reliability, speed and quantitative data are required, such as seed testing, field surveys, identification of virus reservoirs, screening of germplasm for sources of resistance, and disease forecasting. ACKNOWLEDGEMENTS

This research was supported by a grant from National Clonal Germplasm Repository. We also thank the USDA National Clonal Germplasm Repository in Davis, CA for providing us with isolates for all viruses under study. REFERENCES Altschul S.F., Madden T.L., Schäffer A.A., Zhang J., Zhang Z., Miller W., Lipman D.J., 1997. Gapped BLAST and PSIBLAST: a new generation of protein database search programs. Nucleic Acids Research 25: 3389-3402. Bertozzi T., Alberts E., Sedgley M., 2002. Detection of Prunus necrotic ringspot virus in almond: effect of sampling time

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