Using a GFP-labeled Stagonospora nodorum strain as a DNA extraction efficiency standard in plant disease diagnosis

Using a GFP-labeled Stagonospora nodorum strain as a DNA extraction efficiency standard in plant disease diagnosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Using a GFP-labeled Stagonospora nodorum strain as a DNA extraction efficiency standard in plant disease diagnosis Heting Fu, Yalong Yang, Kher Zahr, Shiming Xue, Junye Jiang, Michael Harding, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3922075/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 May, 2024 Read the published version in Crop Protection → Version 1 posted You are reading this latest preprint version Abstract A Stagonospora nodorum strain named DPGZL-2023 was created by transferring a green florescent protein (GFP) gene into the genome of the S. nodorum strain Sn15. DPGZL-2023 showed a similar pathogenicity as Sn15 but carried a strong GFP activity. A qPCR primers/probe set named P-GFP, targeting the GFP sequence, was designed. Using P-GFP, qPCR analysis was conducted on DNA extracted from replicated samples of DPGZL-2023 conidia, and confirmed that DPGZL-2023 could be used to characterize the variation in replicated DNA extractions. Conidia of DPGZL-2023 were used to spike soil samples inoculated with the canola clubroot pathogen Plasmodiophora brassicae , canola stem samples infected with the blackleg pathogens Leptosphaeria biglobosa and/or L. maculans and wheat/barley samples infected with Xanthomonas translucens pv. translucens (Xtt) or X. translucens pv. undulosa (Xtu). Duplex qPCR using P-GFP and a primers/probe set specific to P. brassicae , triplex qPCR using P-GFP and primers/probe sets specific to L. biglobosa and L. maculans , and triplex qPCR using P-GFP and primers/probe sets specific to Xtt and Xtu were conducted. The results indicated that DPGZL-2023 could be used as a standard for DNA extraction efficiency in qPCR-based plant disease diagnosis. Adding DPGZL-2023 conidia to plant or soil samples prior to DNA extraction, and subsequent use of the P-GFP detection control, provided an added control that could distinguish truly negative from false-negative qPCR results. Clubroot Blackleg Bacterial leaf streak Xanthomonas translucens pv. undulosa Xtt Xtu Figures Figure 1 Figure 2 Introduction Plant diseases limit the production and quality of crops. It was estimated that 20–40% of global crop production is lost due to diseases (Strange 2012 ) at a cost of approximately USD $ 220 billion every year (FAO 2019 ). Early pathogen detection and disease diagnosis is a foundational component of pest management programs and mitigation of crop losses (Sankarana et al. 2010 ). Improved diagnostic capacity helps minimize crop loss to pests. In Canada, Alberta’s crop industry is valued at $ 5 billion. A modest production gain of 1% through improved diagnostics would translate into an additional $ 50 million a year in farm gate revenue. Among the methods for plant disease diagnosis, molecular sequence-based methods, such as PCR, are the most sensitive and specific, and are commonly used in most plant diagnostics labs (Henson and French 1993 ; Botella 2022 ). For PCR-based diagnostic methods, the initial DNA (or RNA) extraction step can ultimately determine the success or failure of the amplification protocol. This is because poor DNA yield, or excessive presence of inhibitors, inevitably leads to an inaccurate quantification of the target, or worse, false-negative results (Botella 2022 ). In many plant diagnostic labs, testing multiple samples for the presence of a specific pathogen via qPCR is a routine task. Larger sample numbers occur in labs integrated with disease/pest monitoring or surveillance units and tasked with evaluation of large numbers of survey samples. For diagnostic work integrated with surveillance or monitoring, the samples may include analyses of plant tissues from different locations, species, cultivars, growth stages or organs, and invariably contain non-target pathogens. Additionally, some may be soil samples comprised of different soil types, each differing in abiotic composition (water, clay, macro- and micro-nutrients), and biotic composition (organic material and microorganisms). This diversity in composition can all influence the efficiency of the DNA extraction step which will, in turn, affect the PCR results on the target. In addition, measurement of the concentration of total DNA derived from these samples is not informative for the PCR results on the target. Furthermore, for many soil samples or dried plant samples, the target pathogen might be present but the extracted total DNA was at very low concentration that couldn’t be measured by a spectrophotometer. From these samples, true negative qPCR results couldn’t be differentiated from false negative results. An independent, positive DNA extraction control or standard could provide information on the DNA extraction efficiency across samples. In this study, we developed a DNA extraction control that was intended to be used in conjunction with qPCR diagnosis. It consisted of a green florescent protein gene (GFP)-labeled Stagonospora nodorum strain named DPGZL-2023 and a qPCR primers/probe set named P-GFP, targeting the GFP sequence. Conidia of DPGZL-2023 were added into plant or soil samples before DNA extraction to establish a reference for DNA extraction efficiencies among samples. Primer/probe sets for the target pathogens, and P-GFP, were used in multiplex reactions that concurrently report both the DNA extraction efficiency and the target signal. The quantification cycle (Cq) values of P-GFP reported the DNA extraction efficiency in each sample, identifying those with inferior DNA extraction and possible false negative results for the target. Herein, we describe the development of this DNA extraction control system and demonstrate the usefulness of this system in qPCR-based diagnoses of plant diseases. Materials and methods Chemicals and standard techniques All chemicals and instruments were purchased from Fisher Scientific Canada (Ottawa, ON) unless otherwise specified. All primers and probes were synthesized by Integrated DNA Technologies (Coralville, IA). PCR was conducted in Promega PCR master mix with a ProFlex PCR system. Each 20-µL PCR reaction contained 0.25 µM of each primer and 20 ng template DNA. The PCR program consisted of an initial denaturation at 95°C for 3 min, followed by 35 cycles of denaturation at 95°C for 30 s, annealing at 58°C for 45 s and extension at 72°C for 1 min, and a final extension at 72°C for 5 min. Probe-based qPCR were conducted in PrimeTime gene expression master mix (Integrated DNA Technologies) in a CFX96 touch real-time PCR detection system (Bio-Rad Canada, Mississauga, ON). Each 20-µL qPCR reaction contained 0.5 µM of each primer, 0.18 µM of each probe and 2 µL of each DNA template regardless of the concentrations. Each qPCR reaction was conducted with three technical replicates. In each 96-well PCR plate, three replicates of negative-control reactions were also included, in each of which 2 µL of water was used as template. The qPCR program consisted of an initial denaturation at 95°C for 3 min, followed by 40 cycles of denaturation at 95°C for 10 s and annealing/extension at 60°C for 30 s. Plant and pathogen materials The spring wheat ( Triticum aestivum ) cultivar Harvest was used as the host of Stagonospora nodorum and Xanthomonas translucens pathovar (pv.) translucens (Xtt) and X. translucens pv. undulosa (Xtu). Maintaining of wheat plants followed Feng et al. ( 2012 ). Canola ( Brassica napus ) cultivar Westar was used as the host of the clubroot pathogen Plasmodiophora brassicae . The canola plants were maintained under the same conditions as the wheat plants. The S. nodorum strain Sn15 was purchased from the Fungal Genetics Stock Center (FGSC, http://www.fgsc.net ) and used as the wild-type. The fungus was maintained on V8-agar plates (20% V8 juice, 1.5% agar and 0.15% CaCO 3 ) under continuous light at 25°C. When needed, conidia were collected from 10-d old V8-agar plates. Long-term cultures of Sn15 were kept in -80°C as conidia suspensions in 16% glycerol. A P. brassicae population (unknown pathotype) was used in this study in the form of root galls on the cultivar Westar that were maintained in a -20°C freezer. Fungal transformation The vector gGFP was purchased from FGSC, which carries a GFP gene consisting of the open reading frame of a modified jellyfish ( Aequorea victoria ) GFP gene (SGFP) and the Aspergillus nidulans gpd promoter (Maor et al. 1998 ). Integration of the GFP gene into the Sn15 genome, including plasmid DNA preparation, protoplast production and fungal transformation followed Feng et al. ( 2012 ) with a modification that 2.5 × 10 9 protoplasts suspended in 200 µL STC buffer were supplemented with 30 µg unlinealized gGFP plasmid DNA. Selection media was 4% potato dextrose agar (PDA) containing 75 µg mL − 1 hygromycin-B (Millipore Sigma Canada, Oakville, ON). The regenerated transformants were transferred from the selection media within 14 days after transformation onto fresh V8-agar plates containing the same concentration hygromycin-B as in the selection media. Sporulation and long-term culturing of the transformants were performed with the same procedure as for Sn15. Single spore isolates were obtained by spreading diluted conidia on 1% water agar and then selecting colonies generated by single spores under a M205C dissection microscope (Leica, Wetzlar, Germany). GFP assay GFP activity in the colonies and the conidia suspensions of the transformants was examined with a DR195M Dark Reader Transilluminator (Mandel, Guelph, ON). GFP activity in mycelia and conidia, in vitro or in planta , of a selected transformant was examined under an AxioImager M2 microscope equipped with a GFP filter and an AxioCam506 camera (Carl Zeiss Canada, North York, ON). Pathogenicity test The pathogenicity of the Sn15 strain and selected transformants was assayed on wheat seedlings using a spray-inoculation method with an inoculum concentration of 3.75 × 10 6 conidia mL − 1 . The detailed techniques for collecting conidia, inoculation and plant maintaining after inoculation followed Feng et al. ( 2012 ). After the pathogenicity test, one transformant, named DPGZL-2023, was selected for subsequent studies. qPCR primer design The PCR primer pair developed by Sasmono et al. ( 2003 ) was named P-Seq in this study and used to amplify a GFP fragment from the Sn15 transformants, which would confirm the integration of GFP gene into the Sn15 genome. The PCR product was sequenced. Based on the resultant sequence, a qPCR primers/probe set was designed using Primer 3 ( https://primer3.ut.ee ) and named P-GFP. The probe was labelled with the fluorescent dye Cyanine5 (Cy5). The usefulness of the GFP-labelled Sn15 strain (DPGZL-2023) in PCR diagnosis of plant diseases was tested in three plant pathosystems: (1) canola clubroot caused by P. brassicae , (2) canola blackleg caused by L. biglobosa and L. maculans and (3) bacterial leaf streak on barley and wheat caused by Xtt and Xtu, respectively. For clubroot detection, primers/probe set P-Pbr, consisting of the primer pair CrqF2/CrqR2 (Zahr et al. 2021 ) and the probe PB1 (Deora et al. 2015 ), were used. For blackleg detection, primers/probe set P-Lb and P-Lm developed by Fu et al. ( 2023 ), specific to L. biglobosa and L. maculans , respectively, were used. For Xtt detection, primers/probe set P-Xtt (Fu et al. 2024 ) was used. For Xtu detection, a primers/probe set was designed in this study according to the target sequence of the Xtu-specific PCR primer pair XtuF/XtuR developed by Alvandi et al. ( 2023 ) and named P-Xtu. The detailed information of primers and probes is listed in Table 1 . Table 1 Primers and probes used in this study Name Sequences (5’-3’) 1 Reference P-Seq F CTGGTCGAGCTGGACGGCGACG Sasmono et al. ( 2003 ) R CACGAACTCCAGCAGGACCATG P-GFP F AGAACGGCATCAAGGTGAAC This study P /5Cy5/CGATGTTGT/TAO/GGCGGATCTTG/3IAbRQSp/ R TGCTCAGGTAGTGGTTGTCG P-Pbr F CTAGCGCTGCATCCCATATC Zahr et al. ( 2021 ) P 56-FAM/CCATGTGAA/ZEN/CCGGTGAC/3IABkFQ Deora et al. ( 2015 ) R TGTTTCGGCTAGGATGGTTC Zahr et al. ( 2021 ) P-Xtt F GAAGCCTGACGAGATGGCG Fu et al. ( 2024 ) P /56-FAM/AGAAATCCA/ZEN/GGGCCATCGTC/3IABkFQ/ R TGCCTACGCCGGAATACCG P-Xtu F CTCGCTGCTCAGTTGGGG This study P /5HEX/CAAACGGAC/ZEN/TCACTTCGCC/3IABkFQ/ R GTTCCGGTCGCCACACTG P-Lb F GAAGAATGGCAAAATCACAGG Fu et al. ( 2023 ) P /56-FAM/AGGAAGAAG/ZEN/CAGCCATAGGC/3IABkFQ/ R AGCTCTGCGCGACCTTTT P-Lm F CCTCACACTCTCGACCCCTA Fu et al. ( 2023 ) P /5HEX/CACAGCCAT/ZEN/ATCATCCTGCA/3IABkFQ/ R GCATGTTCTTGAACCGCTAC 1 F = forward primer; R = reverse primer; P = probe DNA extraction from Stagonospora nodorum conidia, soil or plant samples DNA extraction from S. nodorum conidia, soil or plant samples was performed with a Qiacube (Qiagen Canada, Toronto, ON). Depending on the sample types, and the purposes of experiments, three DNA extraction methods were used. In Method-1, DNeasy Plant Pro Kits (Qiagen Canada) were used following the manufacturer’s instructions. In Method-2, DNeasy Plant Pro Kits were used, but the tissue lysate generated from the lysing step was aliquoted into three tubes and each tube was subjected to one DNA extraction with the same procedure as in Method-1. In Method-3, DNeasy PowerSoil Pro Kits (Qiagen Canada) were used following the manufacturer’s instructions. For each method, the resultant DNA was eluted in 50 µL elution buffer included in the kits. Assessment of the usefulness of DPGZL-2023 as a DNA extraction control in qPCR diagnosis DNA was extracted from 3.75 × 10 7 conidia (100 µL of suspension with a concentration of 3.75 × 10 8 conidia per mL) obtained from strain DPGZL-2023 using Method-1. DNA concentration was measured with a NanoDrop-1000. From the extracted DNA, a set of 10× serial dilutions was prepared. Using the dilutions as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. The obtained data were used to generate a qPCR standard curve for P-GFP. DNA was extracted from five samples of 3.75 × 10 5 conidia (100 µL of suspension with a concentration of 3.75 × 10 6 conidia per mL) obtained from strain DPGZL-2023 using Method-1. Using the five DNA samples as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. In another analysis, Method-1 was used to extract DNA from 3.75 × 10 5 DPGZL-2023 conidia (100 µL of suspension with a concentration of 3.75 × 10 6 conidia per mL) and, in a separate extraction, DNA was collected from ten 0.5-cm diameter discs cut from canola leaves. A set of 2× serial dilutions was prepared from the canola DNA. Using the DPGZL-2023 DNA mixed with each of the canola DNA dilutions as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. The obtained data from the two analyses were used to evaluate variations in the quantity of DNA between replicates. Canola leaf discs (0.5-cm diameter) were prepared in batches of 30, six, or three leaf discs, and each batch was spiked with 1.125 × 10 6 conidia (30 µL of suspension with a concentration of 3.75 × 10 7 conidia per mL) of DPGZL-2023. DNA was extracted from each of the spiked leaf batch with Method-2, which would generate three DNA samples from each spiked leaf batch. Using the DNA samples as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. The obtained data were used to evaluate whether the tissue lysing step in the DNA extraction process caused DNA quantity variation among replicated DNA extractions. Autoclaved soil samples and resting spore suspensions of the canola clubroot pathogen P. brassicae were prepared as described by Zahr et al ( 2021 ). Five 100-mg soil samples were prepared, each of which was spiked with 3.75 × 10 5 DPGZL-2023 conidia (10 µL of suspension with a concentration of 3.75 × 10 7 conidia per mL) and 3.75 × 10 5 P. brassicae resting spores (10 µL of suspension with a concentration of 3.75 × 10 7 resting spores per mL). DNA was extracted from these five samples with Method-3. Using the DNA samples as the templates, duplex qPCR analyses were conducted with the primers/probe sets P-GFP and P-Pbr. The obtained data were used to evaluate the usefulness of DPGZL-2023 as a DNA extraction control in duplex qPCR. Four canola stem samples (Canola-1 to Canola-4) showing blackleg symptoms were collected from fields in Sturgeon County (Canola-1), Wheatland County (Canola-2 and Canola-3) and St. Paul County (Canola-4) of Alberta. From each sample, a 300-mg subsample was prepared. Each subsample was spiked with 1.125 × 10 6 DPGZL-2023 conidia (30 µL of suspension with a concentration of 3.75 × 10 7 ). DNA was extracted from the spiked samples with Method-2. Using the DNA samples as the templates, triplex qPCR analyses were conducted with the primers/probe sets P-GFP, P-Lb and P-Lm. The obtained data were used to evaluate the usefulness of DPGZL-2023 as a DNA extraction control in triplex qPCR for the detection of fungal pathogens. One wheat and two barley (Barley-1 and Barley-2) samples showing bacterial leaf streak symptoms were collected from alternative fields in the vicinities of Edmonton. From each plant, a leaf sample consisting of six leaf discs (0.5-cm diameter) was prepared. Each leaf sample was spiked with 1.125 × 10 6 DPGZL-2023 conidia (30 µL of suspension with a concentration of 3.75 × 10 7 ). DNA was extracted from the spiked samples with Method-2. Using the DNA samples as the templates, triplex qPCR analyses were conducted with the primers/probe sets P-GFP, P-Xtt and P-Xtu. The obtained data were used to evaluate the usefulness of DPGZL-2023 as a DNA extraction control in triplex qPCR for the detection of bacterial pathogens. Data analysis The qPCR standard curve was constructed by regression analysis using the SAS software (version 9.4; SAS Institute, Cary, NC). SAS was also used to evaluate data from each experiment by analysis of variance (ANOVA). Differences between qPCR reactions were assessed with the Tukey's multiple comparison test at P ≤ 0.05. Results Transformant identification Three transformants were selected from one transformation experiment and purified by the single spore method. Hyphae from the three transformants and the three single-spore isolates showed similar GFP signals under the microscope (data not shown). The presence of the GFP coding sequence in the three single-spore isolates was confirmed by PCR using the primer pair P-Seq (data not shown). One single spore isolate named DPGZL-2023 was used in further studies. DPGZL-2023 was deposited to the Alberta Plant Health Lab culture collection and is available free to other researchers upon request. GFP activity and pathogenicity of DPGZL-2023 Under the Dark Reader Transilluminator, green florescence was observed from the colony of DPGZL-2023 (Fig. 1 a). Under the microscope, green florescence was observed from the conidia (Fig. 1 b) in vitro and conidia and hyphae in planta (Fig. 1 c). On wheat cultivar Harvest, DPGZL-2023 had similar pathogenicity as the wild type (data not shown). qPCR analysis on the repeatability of the primers/probe set P-GFP Sequencing the PCR product of P-Seq from the vector DNA resulted in a 531-bp clean sequence, identical to nucleotides (nt) 515–1045 of the cloning vector pCEBN-GFP (GenBank accession number MN781141). Based on this sequence, the qPCR primers/probe set P-GFP was designed. A qPCR standard curve was constructed for P-GFP based on the Cq values from a serial dilution set of DPGZL-2023 DNA (Fig. 2 ). The efficiency of P-GFP was 0.97. The standard curve provided a reference on how many DPGZL-2023 conidia should be used to spike a sample to be tested for pathogens. DNA was extracted from five replicates of 3.75 × 10 5 DPGZL-2023 conidia. qPCR was conducted on these five DNA samples using P-GFP. Differences in the Cq values were found among these five replicates (Table 2 ). This result indicated that variation or a part of the variation in Cq values among replicates was predetermined in the stages before qPCR set up. Table 2 qPCR analysis of DNA from the Stagonospora nodorum strain DPGZL-2023 Rep 1 Cq 2 SD 3 Mean 4 1 24.53 24.55 24.50 0.03 24.53a 2 24.51 24.48 24.42 0.05 24.47a 3 24.36 24.35 24.29 0.04 24.33b 4 24.17 24.22 24.24 0.04 24.21c 5 24.11 24.10 24.12 0.01 24.11d 1 DNA was extracted from five replicates of conidia samples with each sample containing 3.75 × 10 5 conidia. The extracted DNA from each conidia sample was dissolved in 50 µL water. 2 The quantification cycle (Cq) values of three technical replicates for each DNA sample. Two µL of DNA was used in each 20-µL qPCR reaction, which was equivalent to the DNA from 1.5 × 10 4 conidia. 3 SD = standard deviation. 4 Means followed by the same letter do not differ based on Tukey's multiple comparison test at P ≤ 0.05. The stages before qPCR included sample preparation and DNA extraction. To verify that DNA extraction was the factor causing the Cq variation among DNA samples, DPGZL-2023 DNA was mixed with different aliquots of canola DNA and then the mixtures were used as templates in qPCR analysis using P-GFP. No Cq difference was observed among the DNA samples (Table 3 ). This result indicated that the DNA extraction, rather than sample preparation, was responsible for the observed Cq differences among DNA samples. Table 3 qPCR analysis of DNA samples containing a mixture of Stagonospora nodorum DNA and canola DNA Sno 1 Canola 1 Cq 2 SD 3 Mean 4 1× 1× 24.28 24.42 24.46 0.09 24.39a 1× 1/2× 24.31 24.28 24.18 0.07 24.26a 1× 1/4× 24.33 24.42 24.16 0.13 24.30a 1× 1/8× 24.26 24.24 24.26 0.01 24.25a 1× 1/16× 24.38 24.42 24.31 0.06 24.37a 1× 0 24.31 24.26 24.22 0.05 24.26a 1 DNA was extracted from 3.75 × 10 5 conidia of the S. nodorum strain DPGZL-2023 and ten 0.5-cm diameter leaf discs of canola. Both DNA samples were dissolved in 50 µL water. A set of two-time serial dilutions were prepared from the canola DNA. 2 The quantification cycle (Cq) values of three technical replicates for each DNA sample. The template in each 20-µL qPCR reaction consisted of 2 µL of the Sno DNA and 2 µL of each of the serial dilutions of canola DNA. 3 SD = standard deviation. 4 Means followed by the same letter do not differ based on Tukey's multiple comparison test at P ≤ 0.05. The first step of DNA extraction using the Qiagen kits is sample lysing. After centrifugation of the lysate, the supernatant was transferred into a new tube for the subsequent DNA extraction. To evaluate whether the sample lysing step caused the Cq variation among DNA samples, DNA was extracted from aliquots of lysates from a mixture consisting of DPGZL-2023 conidia and canola leaves. qPCR analysis using P-GFP indicated that there was no Cq variation among DNA samples extracted from aliquots of the same lysate, although variation was still present among DNA samples extracted from different lysate preparations (Table 4 ). This result indicated that the sample lysing step in DNA extraction caused the Cq value variation among DNA samples. Table 4 qPCR analysis of DNA extracted from samples consisting of Stagonospora nodorum conidia and canola leaves DNA 1 Rep 1 Cq 2 SD 3 Mean 4 A 1 25.23 25.40 25.29 0.09 25.31b 2 25.11 25.23 25.22 0.07 25.19b 3 25.28 25.32 25.26 0.03 25.28b B 1 25.70 25.86 25.79 0.08 25.78a 2 25.78 25.71 25.60 0.09 25.70a 3 26.08 25.51 25.68 0.19 25.76a C 1 25.63 25.72 25.57 0.08 25.64a 2 25.74 25.80 25.89 0.08 25.81a 3 25.70 25.70 25.79 0.05 25.73a 1 Canola leaf discs (0.5-cm diameter) were prepared. Thirty (A), six (B) or three (C) leaf discs were spiked with 1.125 × 10 6 conidia of the S. nodorum strain DPGZL-2023. After the tissue homogenization step of DNA extraction, the supernatant of A, B or C was aliquoted into three tubes (Rep 1–3). DNA was extracted from each tube and dissolved in 50 µL water. 2 The quantification cycle (Cq) values of three technical replicates for each DNA sample. Two µL of DNA was used in each 20-µL qPCR reaction. 3 SD = standard deviation. 4 Means followed by the same letter do not differ based on Tukey's multiple comparison test at P ≤ 0.05. qPCR analysis on the usefulness of DPGZL-2023 as DNA extraction control in plant disease diagnosis The usefulness of DPGZL-2023 as a DNA extraction control was tested in qPCR diagnosis of the clubroot pathogen P. brassicae . DNA was extracted from mixtures of DPGZL-2023 conidia and clubroot resting spores and used in duplex qPCR with the primers/probe sets P-GFP and P-Pbr. Variations in the Cq values of P-GFP, as well as P-Pbr, were observed among the replicates (Table 5 ). Nevertheless, the trend of P-GFP Cq fluctuation among replicates was identical to that of P-Pbr, suggesting that the Cq values of P-GFP could be used as a DNA extraction control in diagnosis of clubroot and the control function could be either qualitative or quantitative. Table 5 Duplex qPCR analysis of DNA extracted from soil samples containing conidia of Stagonospora nodorum strain DPGZL-2023 (P-GFP) and resting spores of Plasmodiophora brassicae (P-Pbr) P-GFP P-Pbr Rep 1 Cq 2 SD 3 Mean 4 Cq 2 SD 3 Mean 4 1 22.58 22.50 22.45 0.07 22.51a 23.25 23.22 23.14 0.06 23.20a 2 22.39 22.33 22.36 0.03 22.36b 23.07 23.01 23.00 0.04 23.03b 3 22.37 22.35 22.32 0.03 22.35bc 23.07 23.05 23.02 0.03 23.05b 4 22.38 22.32 22.27 0.06 22.32bc 23.04 23.00 22.89 0.08 22.98b 5 22.28 22.30 22.22 0.04 22.27c 22.85 22.85 22.95 0.06 22.88c 1 DNA was extracted from five replicates with each replicate consisting of 3.75 × 10 5 Sno conidia and 3.75 × 10 5 Pbr resting spores. DNA from each replicate was dissolved in 50 µL water. 2 The quantification cycle (Cq) values of three technical replicates for each DNA sample. Two µL of DNA was used in each 20-µL duplex qPCR reaction. 3 SD = standard deviation. 4 Means followed by the same letter do not differ based on Tukey's multiple comparison test at P ≤ 0.05. The usefulness of DPGZL-2023 as a DNA extraction control was also tested in qPCR diagnosis of the two canola blackleg pathogens L. biglobosa and L. maculans . DNA was extracted from four symptomatic canola stem samples spiked with DPGZL-2023 conidia and used in triplex qPCR with the primers/probe sets P-GFP, P-Lb and P-Lm. Leptosphaeria maculans was detected from the sample Canola-1 and L. biglobosa was detected from Canola-2; Both L. maculans and L. biglobosa were detected from Canola-3 and Canola-4 (Table 6 ). Among the three DNA replicates from each lysate, no Cq difference was observed for all the three primers/probe sets. However, for each of the three primers/probe sets, Cq differences were observed among plant samples. While such differences of P-Lb and P-Lm Cq values could be primarily due to different infection levels in the stems, the difference of P-GFP values was due to the lysing process of DNA extraction. Table 6 Triplex qPCR analysis of DNA extracted from canola stem samples for characterization of the blackleg pathogens Leptosphaeria biglobosa and L. maculans P-GFP 2 P-Lb 2 P-Lm 2 Rep 1 SD Mean SD Mean SD Mean Canola-1 1 0.05 24.98cd 0.03 24.76ab 2 0.07 25.04c 0.04 24.78ab 3 0.02 25.03c 0.11 24.81a Canola-2 1 0.03 25.85ab 0.05 26.30a 2 0.06 25.97a 0.06 26.51a 3 0.14 25.75ab 0.21 26.31a Canola-3 1 0.04 25.62b 0.03 25.60bc 0.04 24.62bc 2 0.14 25.80ab 0.05 25.69b 0.09 24.71abc 3 0.12 25.66b 0.09 25.63b 0.07 24.59c Canola-4 1 0.09 24.68e 0.09 25.28c 0.10 23.06d 2 0.20 24.77de 0.17 25.40bc 0.07 23.12d 3 0.10 24.77de 0.12 25.27c 0.08 23.05d 1 A 300-mg subsample from each stem sample was prepared. Each subsample was spiked with 1.125 × 10 6 conidia of the S. nodorum strain DPGZL-2023. After the tissue homogenization step of DNA extraction, the supernatant of each subsample was aliquoted into three tubes (Rep 1–3). DNA was extracted from each tube and dissolved in 50 µL water. 2 The mean quantification cycle (Cq) values of three technical replicates for each DNA sample. Two µL of DNA was used in each 20-µL qPCR reaction. SD = standard deviation. Means followed by the same letter do not differ based on Tukey's multiple comparison test at P ≤ 0.05. The usefulness of DPGZL-2023 as a DNA extraction control was further tested in qPCR diagnosis of the two wheat bacterial leaf streak (BLS) pathogens Xtt and Xtu. DNA was extracted from symptomatic barley and wheat leaves spiked with DPGZL-2023 conidia and used in triplex qPCR with the primers/probe sets P-GFP, P-Xtt and P-Xtu. Xtu was detected from the wheat sample; Xtt was detected from one barley sample; Both Xtt and Xtu were detected from the other barley sample (Table 7 ). Among the three DNA replicates from each lysate, no Cq difference was observed for all the three primers/probe sets. However, for each of the three primers/probe sets, Cq differences were observed among plant samples. Again, while such differences of P-Xtt and P-Xtu Cq values could be primarily due to different infection levels in the leaves, the difference of P-GFP values was due to the lysing process of DNA extraction. Table 7 Triplex qPCR analysis of DNA extracted from wheat or barley samples for characterization of the bacterial leaf streak pathovars Xtt and Xtu in wheat and barley P-GFP 2 P-Xtt 2 P-Xtu 2 Rep 1 SD Mean SD Mean SD Mean Wheat 1 0.02 24.22b 0.09 20.15b 2 0.01 24.15b 0.06 19.99b 3 0.12 24.19b 0.17 19.97b Barley 1 1 0.06 23.43c 0.14 17.34b 0.18 33.60a 2 0.03 23.42c 0.07 17.38b 0.16 33.61a 3 0.06 23.46c 0.03 17.45b 0.07 33.79a Barley 2 1 0.04 24.48a 0.12 21.17a 2 0.02 24.46a 0.20 21.08a 3 0.07 24.49a 0.20 21.28a 1 Six leaf discs (0.5-cm diameter) from each plant sample were prepared. Each leaf sample was spiked with 1.125 × 10 6 conidia of the S. nodorum strain DPGZL-2023. After the tissue homogenization step of DNA extraction, the supernatant of each plant sample was aliquoted into three tubes (Rep 1–3). DNA was extracted from each tube and dissolved in 50 µL water. 2 The mean quantification cycle (Cq) values of three technical replicates for each DNA sample. Two µL of DNA was used in each 20-µL qPCR reaction. SD = standard deviation. Means followed by the same letter do not differ based on Tukey's multiple comparison test at P ≤ 0.05. Discussion GFP has been used as a reporter marker because it provides a visual means to identify genetically engineered cells (Lippincott-Schwartz and Patterson 2003 ). The wild-type GFP has a major absorption maximum at 397 nm and a minor excitation peak at 475 nm (Yang et al. 1996 ). Modified forms of GFP, including the SGFP used in the current study, have a “red shift” from excitation maxima of 395 and 470 nm to a maximum of 488 nm (Lorang et al. 2001 ), which enables the GFP activity to be detected with a blue-light Dark Reader Transilluminator. The DPGZL-2023 strain generated in this study can produce a strong GFP signal that could be early detected in vitro and in planta. Having a similar pathogenicity as the wild-type, DPGZL-2023 may be useful as a tool to study the pathogenicity of S. nodorum . In plant diagnostics labs, negative results are commonly obtained from tested samples. A negative PCR results can be explained by three conditions: 1) absence of the target (true negative), 2) failure of the PCR protocol to amplify the target (false negative), or 3) poor DNA extraction (false negative). All diagnostic tests should include at least one positive control and one negative control. Generally, the positive control used in PCR tests is “control” of the PCR/qPCR system rather than the template DNA. Such positive controls can be DNA from the target organism or synthesized DNA containing the target sequence. Adding this control DNA after extraction allows for monitoring of inhibition within the assay and rule out false negatives due to a failure of the PCR reaction, but cannot detect a false negative due to a DNA extraction error. The method described herein can be used as a second positive control, or standard, to report the success or efficiency of DNA extraction. Using both an internal positive control, and a DNA extraction control, allows one to rule out both causes of a false negative so that true negative results can be confirmed. In our hands, the control agent has been easy to prepare and the measurement of DNA extraction reported with a high accuracy. The GFP-labeled S. nodorum strain described here has advantages for use as such a DNA extraction control. 1) This fungus can rapidly produce large numbers of conidia on commonly used agar media within 1–2 weeks, and the conidia are easily purified, i.e. without mycelia, 2) The conidia can be easily quantified with a hemocytometer due to the size, the shape and the color of the conidia and 3) the DNA sequence of the GFP gene (from jelly fish) is unlikely present in plants and plant-associated microorganisms including plant pathogens. Other evidences for the user-friendly nature of GFP-labeled S. nodorum include: 1) S. nodorum can be easily transformed for gene insertion (Feng et al. 2011 , 2012 ; this study) and 2) All the DPGZL-2003 conidia used in this study represented only a portion of conidia produced on one 10-cm petri dish (2 × 10 8 conidia per petri dish). The DPGZL-2023 strain and the primers/probe set P-GFP developed in the current study are especially useful for disease diagnosis from soil samples. The amount of DNA extracted from soil samples could have a large differences ranging from trace amounts, unmeasurable with a spectrophotometer, to large amounts. This can be due to inhibition of DNA accessibility or survival in soil and also influenced by the amount of other non-target organisms present. For quantitative tests, such as population dynamic studies on soilborne pathogens, a DNA extraction control is essential so that fair comparisons and conclusions can be made. This was demonstrated in the current study. However, a preliminary literature search indicated that a control or standard for DNA extraction has never attracted attention or gained favor. DNA extraction efficiency affecting the accuracy of plant disease diagnosis or pathogen quantification has been studied previously (Yang et al. 2021 ), and experimentally confirmed by the current study. In the current study, a Qiacube was used for all DNA extraction which would increase the consistency of DNA yield across different samples compared to a human technician manually employing a DNA extraction kit. However, variation on DNA yield was still present even using the Qiacube. This observation further highlights that caution should always be exercised when interpreting qPCR data if no DNA extraction control was included. In conclusion, the current study emphasized the importance of including a DNA extraction control in qPCR-based plant disease diagnosis. The development of a DNA extraction control system was described, and demonstrated in multiple examples of sample types, and qPCR systems. This system is now a standard used in detection or evaluation of all diagnostic and disease survey/monitoring samples in the Alberta Plant Health Lab. We recommend that other diagnostic labs also adopt this standard in their qPCR diagnostics, population studies and surveillance/monitoring sample evaluations, and are willing to provide the DPGZL-2023 strain to others free of charge, upon request. References Alvandi H, Taghavi SM, Khojasteh M, Rahimi T, Dutrieux C, Taghouti G, Jacques MA, Portier P, Osdaghi E (2023) Pathovar-specific PCR method for detection and identification of Xanthomonas translucens pv. undulosa . Plant Dis 107:2279–2287. https://doi.org/10.1094/PDIS-11-22-2677-SR Botella JR (2022) Point-of-care DNA amplification for disease diagnosis and management. Annu Rev Phytopathol 60:1–20. https://doi.org/10.1146/annurev-phyto-021621-115027 Deora A, Gossen BD, Amirsadeghi S, McDonald MR (2015) A multiplex qPCR assay for detection and quantification of Plasmodiophora brassicae in soil. Plant Dis 99:1002–1009. https://doi.org/10.1094/PDIS-06-14-0608-RE FAO (2019) New standards to curb the global spread of plant pests and diseases. https://www.fao.org/news/story/en/item/1187738/icode/ Feng J, Hwang R, Hwang SF, Gaudet D, Strelkov SE (2011) Molecular characterization of a Stagonospora nodorum lipase gene LIP1. Plant Pathol 60:698–708. https://doi.org/10.1111/j.1365-3059.2011.02434.x Feng J, Li W, Hwang SF, Gossen BD, Strelkov SE (2012) Enhanced gene replacement frequency in KU70 disruption strain of Stagonospora nodorum . Microbiol Res 167:173–178. https://doi.org/10.1016/j.micres.2011.05.004 Fu H, Yang Y, Sarkes A, Harding MW, Feindel D, Feng J (2023) Development of a duplex qPCR system for detection and quantification of the two canola blackleg pathogens Leptosphaeria biglobosa and L. maculans. Plant Dis 107:2808–2815. https://doi.org/10.1094/PDIS-10-22-2308-RE Fu H, Fleitas MC, Sarkes A, Wang L, Yang Y, Zahr K, Harding MW, Feindel D, Kutcher R, Feng J (2024) Detection and differentiation of Xanthomonas translucens pathovars translucens and undulosa from wheat and barley by duplex quantitative PCR. Plant Dis (online first Sep. 5, 2023). https://doi.org/10.1094/PDIS-05-23-0887-SR Henson JM, French R (1993) The polymerase chain reaction and plant disease diagnosis. Ann Rev Phytopathol 31:81–109. https://www.doi.org/10.1146/annurev.py.31.090193.000501 Lippincott-Schwartz J, Patterson GH (2003) Development and use of fluorescent protein markers in living cells. Science 300:87–91. https://doi.org/10.1126/science.1082520 Lorang JM, Tuori RP, Martinez JP, Sawyer TL, Redman RS, Rollins JA, Wolpert TJ, Johnson KB, Rodriguez RJ, Dickman MB, Ciuffetti LM (2001) Green fluorescent protein is lighting up fungal biology. Appl Environ Microbiol 67:1987–1994. https://doi.org/10.1128/AEM.67.5.1987-1994.2001 Maor R, Puyesky M, Horwitz BA, Sharon A (1998) Use of green fluorescent protein (GFP) for studying development and fungal-plant interaction in Cochliobolus heterostrophus. Mycol Res 102:491–496. https://doi.org/10.1017/S0953756297005789 Sankarana S, Mishraa A, Ehsania R, Davis C (2010) A review of advanced techniques for detecting plant diseases. Comput Electron Agr 72:1–13. https://doi.org/10.1016/j.compag.2010.02.007 Sasmono RT, Oceandy D, Pollard JW, Tong W, Pavli P, Wainwright BJ, Ostrowski MC, Himes SR, Hume DA (2003) A macrophage colony-stimulating factor receptor-green fluorescent protein transgene is expressed throughout the mononuclear phagocyte system of the mouse. Blood 101:1155–1163. https://doi.org/10.1182/blood-2002-02-0569 Strange R (2012) Almost 40 per cent of worldwide crops lost to diseases. The Crop Site, http://www.thecropsite.com/articles/1202/almost-40-per-cent-of-worldwide-crops-lost-to-diseases Yang F, Moss LG, Phillips GN (1996) The molecular structure of green fluorescent protein. Nat Biotechnol 14:1246–1251. https://doi.org/10.1038/nbt1096-1246 Yang Y, Zhou Q, Zahr K, Harding MW, Feindel D, Feng J (2021) Impact of DNA extraction efficiency on the sensitivity of PCR-based plant disease diagnosis and pathogen quantification. Eur J Plant Pathol 159:583–591. https://doi.org/10.1007/s10658-020-02189-1 Zahr K, Sarkes A, Yang Y, Ahmed H, Zhou Q, Feindel D, Harding MW, Feng J (2021) Plasmodiophora brassicae in its environment: effects of temperature and light on resting spore survival in soil. Phytopathology 111:1743–1750. https://doi.org/10.1094/PHYTO-09-20-0415-R Cite Share Download PDF Status: Published Journal Publication published 31 May, 2024 Read the published version in Crop Protection → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3922075","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271232439,"identity":"33dc7c44-3714-44f1-8a6d-af6fdd5577b7","order_by":0,"name":"Heting Fu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Heting","middleName":"","lastName":"Fu","suffix":""},{"id":271232440,"identity":"d8393fec-ba07-45a4-85fd-1cd9a74e4cee","order_by":1,"name":"Yalong Yang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yalong","middleName":"","lastName":"Yang","suffix":""},{"id":271232441,"identity":"058c8521-800d-40cc-a56f-6c36fc659e4a","order_by":2,"name":"Kher Zahr","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kher","middleName":"","lastName":"Zahr","suffix":""},{"id":271232442,"identity":"f46493e4-9cd5-4d3c-81d8-23d77a793a35","order_by":3,"name":"Shiming Xue","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Shiming","middleName":"","lastName":"Xue","suffix":""},{"id":271232443,"identity":"0faf578d-355d-41a7-9a4d-e6ff39f6f371","order_by":4,"name":"Junye Jiang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Junye","middleName":"","lastName":"Jiang","suffix":""},{"id":271232444,"identity":"f9383818-9b3d-4436-8fd1-a533de5a6462","order_by":5,"name":"Michael Harding","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Harding","suffix":""},{"id":271232445,"identity":"84512134-c7bd-498e-b61a-9db4a73e2a2d","order_by":6,"name":"David Feindel","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Feindel","suffix":""},{"id":271232446,"identity":"3c0bca84-d034-42e7-a3c7-0412269475a7","order_by":7,"name":"Jie Feng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIie2RsQqDMBCGTwQnIWu6tK8QETrWV1GEPoODgyDoUuravY9Q6HwScAp0dXBIF2e7dJTG2rlxLDQfdzkC9/EHAmAw/CBWro5ENZnvuFARqlfZUuXNpDBcqtiljYBJt7vczg2FtANSajQrd0JA0cfXtt9TaHqgItQpLrMfBY+3rfAZOBwYaBUyQD3y2D9NyqgUIrUpAHXGd4wcPGkVSqHaFIchNjykrRPJ6Ni7tNWkeBW/S0x5QCqOODy7Nak0KV42/0WUTe9R5X7fV2w+MwCC2mWDwWD4U16EPEtpLPKGNAAAAABJRU5ErkJggg==","orcid":"","institution":"Alberta Agriculture and Rural Development","correspondingAuthor":true,"prefix":"","firstName":"Jie","middleName":"","lastName":"Feng","suffix":""}],"badges":[],"createdAt":"2024-02-02 21:05:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3922075/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3922075/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1016/j.cropro.2024.106789","type":"published","date":"2024-06-01T00:33:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50822145,"identity":"a38fd0a3-8581-47c7-bfa2-312515db37c7","added_by":"auto","created_at":"2024-02-07 21:51:10","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2527365,"visible":true,"origin":"","legend":"\u003cp\u003eGreen florescence protein activity on the GFP-labelled \u003cem\u003eS. nodorum\u003c/em\u003e. (a), upper panel shows colonies of the wild-type Sn15 (left) and the GFP-labelled strain DPGZL-2023 (right) under natural light, and the lower panel shows colonies visualized using a Dark Reader blue LED transilluminator. (b), Conidia of DPGZL-2023 under a microscope without (upper) or with (lower) a GFP filter. (c), DPGZL-2023 on the epidermis of a wheat leaf 6 hours after inoculation, under a microscope without (left) or with (right) a GFP filter.\u003c/p\u003e","description":"","filename":"FuetalFig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3922075/v1/c63e066b9c715a77b7939273.jpg"},{"id":50822144,"identity":"1e628668-68dc-4aa3-82bc-c5ba64d0f379","added_by":"auto","created_at":"2024-02-07 21:51:10","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":372051,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity of the qPCR primers/probe set P-GFP on a set of dilutions of DNA extracted from conidia of the GFP-labelled \u003cem\u003eS. nodorum\u003c/em\u003e strain DPGZL-2023. The qPCR standard curve was generated from the mean of quantification cycle (Cq) values against log10 of conidia from which the DNA per reaction was derived. The R\u003csup\u003e2\u003c/sup\u003e score of the equation and the efficiency of the primers (E) are indicated over the curve. Efficiency was calculated as E = -1+10\u003csup\u003e(-1/slope)\u003c/sup\u003e. Each data point is shown as mean of three technical replicates ± standard deviation.\u003c/p\u003e","description":"","filename":"FuetalFig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3922075/v1/fd4ebe79108994deb18e99c5.jpg"},{"id":57805709,"identity":"76366048-a324-4f32-a538-b6b0a2f0fffc","added_by":"auto","created_at":"2024-06-06 00:33:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3720543,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3922075/v1/3d9e31bd-6338-41c9-b316-567a49646170.pdf"}],"financialInterests":"","formattedTitle":"Using a GFP-labeled Stagonospora nodorum strain as a DNA extraction efficiency standard in plant disease diagnosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlant diseases limit the production and quality of crops. It was estimated that 20\u0026ndash;40% of global crop production is lost due to diseases (Strange \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) at a cost of approximately USD \u003cspan\u003e$\u003c/span\u003e220\u0026nbsp;billion every year (FAO \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Early pathogen detection and disease diagnosis is a foundational component of pest management programs and mitigation of crop losses (Sankarana et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Improved diagnostic capacity helps minimize crop loss to pests. In Canada, Alberta\u0026rsquo;s crop industry is valued at \u003cspan\u003e$\u003c/span\u003e5\u0026nbsp;billion. A modest production gain of 1% through improved diagnostics would translate into an additional \u003cspan\u003e$\u003c/span\u003e50\u0026nbsp;million a year in farm gate revenue.\u003c/p\u003e \u003cp\u003eAmong the methods for plant disease diagnosis, molecular sequence-based methods, such as PCR, are the most sensitive and specific, and are commonly used in most plant diagnostics labs (Henson and French \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Botella \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For PCR-based diagnostic methods, the initial DNA (or RNA) extraction step can ultimately determine the success or failure of the amplification protocol. This is because poor DNA yield, or excessive presence of inhibitors, inevitably leads to an inaccurate quantification of the target, or worse, false-negative results (Botella \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In many plant diagnostic labs, testing multiple samples for the presence of a specific pathogen via qPCR is a routine task. Larger sample numbers occur in labs integrated with disease/pest monitoring or surveillance units and tasked with evaluation of large numbers of survey samples.\u003c/p\u003e \u003cp\u003eFor diagnostic work integrated with surveillance or monitoring, the samples may include analyses of plant tissues from different locations, species, cultivars, growth stages or organs, and invariably contain non-target pathogens. Additionally, some may be soil samples comprised of different soil types, each differing in abiotic composition (water, clay, macro- and micro-nutrients), and biotic composition (organic material and microorganisms). This diversity in composition can all influence the efficiency of the DNA extraction step which will, in turn, affect the PCR results on the target. In addition, measurement of the concentration of total DNA derived from these samples is not informative for the PCR results on the target. Furthermore, for many soil samples or dried plant samples, the target pathogen might be present but the extracted total DNA was at very low concentration that couldn\u0026rsquo;t be measured by a spectrophotometer. From these samples, true negative qPCR results couldn\u0026rsquo;t be differentiated from false negative results. An independent, positive DNA extraction control or standard could provide information on the DNA extraction efficiency across samples.\u003c/p\u003e \u003cp\u003eIn this study, we developed a DNA extraction control that was intended to be used in conjunction with qPCR diagnosis. It consisted of a green florescent protein gene (GFP)-labeled \u003cem\u003eStagonospora nodorum\u003c/em\u003e strain named DPGZL-2023 and a qPCR primers/probe set named P-GFP, targeting the GFP sequence. Conidia of DPGZL-2023 were added into plant or soil samples before DNA extraction to establish a reference for DNA extraction efficiencies among samples. Primer/probe sets for the target pathogens, and P-GFP, were used in multiplex reactions that concurrently report both the DNA extraction efficiency and the target signal. The quantification cycle (Cq) values of P-GFP reported the DNA extraction efficiency in each sample, identifying those with inferior DNA extraction and possible false negative results for the target. Herein, we describe the development of this DNA extraction control system and demonstrate the usefulness of this system in qPCR-based diagnoses of plant diseases.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eChemicals and standard techniques\u003c/h2\u003e \u003cp\u003eAll chemicals and instruments were purchased from Fisher Scientific Canada (Ottawa, ON) unless otherwise specified. All primers and probes were synthesized by Integrated DNA Technologies (Coralville, IA). PCR was conducted in Promega PCR master mix with a ProFlex PCR system. Each 20-\u0026micro;L PCR reaction contained 0.25 \u0026micro;M of each primer and 20 ng template DNA. The PCR program consisted of an initial denaturation at 95\u0026deg;C for 3 min, followed by 35 cycles of denaturation at 95\u0026deg;C for 30 s, annealing at 58\u0026deg;C for 45 s and extension at 72\u0026deg;C for 1 min, and a final extension at 72\u0026deg;C for 5 min. Probe-based qPCR were conducted in PrimeTime gene expression master mix (Integrated DNA Technologies) in a CFX96 touch real-time PCR detection system (Bio-Rad Canada, Mississauga, ON). Each 20-\u0026micro;L qPCR reaction contained 0.5 \u0026micro;M of each primer, 0.18 \u0026micro;M of each probe and 2 \u0026micro;L of each DNA template regardless of the concentrations. Each qPCR reaction was conducted with three technical replicates. In each 96-well PCR plate, three replicates of negative-control reactions were also included, in each of which 2 \u0026micro;L of water was used as template. The qPCR program consisted of an initial denaturation at 95\u0026deg;C for 3 min, followed by 40 cycles of denaturation at 95\u0026deg;C for 10 s and annealing/extension at 60\u0026deg;C for 30 s.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePlant and pathogen materials\u003c/h2\u003e \u003cp\u003eThe spring wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e) cultivar Harvest was used as the host of \u003cem\u003eStagonospora nodorum\u003c/em\u003e and \u003cem\u003eXanthomonas translucens\u003c/em\u003e pathovar (pv.) \u003cem\u003etranslucens\u003c/em\u003e (Xtt) and \u003cem\u003eX. translucens\u003c/em\u003e pv. \u003cem\u003eundulosa\u003c/em\u003e (Xtu). Maintaining of wheat plants followed Feng et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Canola (\u003cem\u003eBrassica napus\u003c/em\u003e) cultivar Westar was used as the host of the clubroot pathogen \u003cem\u003ePlasmodiophora brassicae\u003c/em\u003e. The canola plants were maintained under the same conditions as the wheat plants. The \u003cem\u003eS. nodorum\u003c/em\u003e strain Sn15 was purchased from the Fungal Genetics Stock Center (FGSC, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fgsc.net\u003c/span\u003e\u003cspan address=\"http://www.fgsc.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and used as the wild-type. The fungus was maintained on V8-agar plates (20% V8 juice, 1.5% agar and 0.15% CaCO\u003csub\u003e3\u003c/sub\u003e) under continuous light at 25\u0026deg;C. When needed, conidia were collected from 10-d old V8-agar plates. Long-term cultures of Sn15 were kept in -80\u0026deg;C as conidia suspensions in 16% glycerol. A \u003cem\u003eP. brassicae\u003c/em\u003e population (unknown pathotype) was used in this study in the form of root galls on the cultivar Westar that were maintained in a -20\u0026deg;C freezer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFungal transformation\u003c/h2\u003e \u003cp\u003eThe vector gGFP was purchased from FGSC, which carries a GFP gene consisting of the open reading frame of a modified jellyfish (\u003cem\u003eAequorea victoria\u003c/em\u003e) GFP gene (SGFP) and the \u003cem\u003eAspergillus nidulans gpd\u003c/em\u003e promoter (Maor et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Integration of the GFP gene into the Sn15 genome, including plasmid DNA preparation, protoplast production and fungal transformation followed Feng et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) with a modification that 2.5 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e protoplasts suspended in 200 \u0026micro;L STC buffer were supplemented with 30 \u0026micro;g unlinealized gGFP plasmid DNA. Selection media was 4% potato dextrose agar (PDA) containing 75 \u0026micro;g mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e hygromycin-B (Millipore Sigma Canada, Oakville, ON). The regenerated transformants were transferred from the selection media within 14 days after transformation onto fresh V8-agar plates containing the same concentration hygromycin-B as in the selection media. Sporulation and long-term culturing of the transformants were performed with the same procedure as for Sn15. Single spore isolates were obtained by spreading diluted conidia on 1% water agar and then selecting colonies generated by single spores under a M205C dissection microscope (Leica, Wetzlar, Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eGFP assay\u003c/h2\u003e \u003cp\u003eGFP activity in the colonies and the conidia suspensions of the transformants was examined with a DR195M Dark Reader Transilluminator (Mandel, Guelph, ON). GFP activity in mycelia and conidia, \u003cem\u003ein vitro\u003c/em\u003e or \u003cem\u003ein planta\u003c/em\u003e, of a selected transformant was examined under an AxioImager M2 microscope equipped with a GFP filter and an AxioCam506 camera (Carl Zeiss Canada, North York, ON).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePathogenicity test\u003c/h2\u003e \u003cp\u003eThe pathogenicity of the Sn15 strain and selected transformants was assayed on wheat seedlings using a spray-inoculation method with an inoculum concentration of 3.75 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The detailed techniques for collecting conidia, inoculation and plant maintaining after inoculation followed Feng et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). After the pathogenicity test, one transformant, named DPGZL-2023, was selected for subsequent studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eqPCR primer design\u003c/h2\u003e \u003cp\u003eThe PCR primer pair developed by Sasmono et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) was named P-Seq in this study and used to amplify a GFP fragment from the Sn15 transformants, which would confirm the integration of GFP gene into the Sn15 genome. The PCR product was sequenced. Based on the resultant sequence, a qPCR primers/probe set was designed using Primer 3 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://primer3.ut.ee\u003c/span\u003e\u003cspan address=\"https://primer3.ut.ee\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and named P-GFP. The probe was labelled with the fluorescent dye Cyanine5 (Cy5).\u003c/p\u003e \u003cp\u003eThe usefulness of the GFP-labelled Sn15 strain (DPGZL-2023) in PCR diagnosis of plant diseases was tested in three plant pathosystems: (1) canola clubroot caused by \u003cem\u003eP. brassicae\u003c/em\u003e, (2) canola blackleg caused by \u003cem\u003eL. biglobosa\u003c/em\u003e and \u003cem\u003eL. maculans\u003c/em\u003e and (3) bacterial leaf streak on barley and wheat caused by Xtt and Xtu, respectively. For clubroot detection, primers/probe set P-Pbr, consisting of the primer pair CrqF2/CrqR2 (Zahr et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and the probe PB1 (Deora et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), were used. For blackleg detection, primers/probe set P-Lb and P-Lm developed by Fu et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), specific to \u003cem\u003eL. biglobosa\u003c/em\u003e and \u003cem\u003eL. maculans\u003c/em\u003e, respectively, were used. For Xtt detection, primers/probe set P-Xtt (Fu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) was used. For Xtu detection, a primers/probe set was designed in this study according to the target sequence of the Xtu-specific PCR primer pair XtuF/XtuR developed by Alvandi et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and named P-Xtu. The detailed information of primers and probes is listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimers and probes used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSequences (5\u0026rsquo;-3\u0026rsquo;)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-Seq\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTGGTCGAGCTGGACGGCGACG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSasmono et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCACGAACTCCAGCAGGACCATG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eP-GFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAACGGCATCAAGGTGAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/5Cy5/CGATGTTGT/TAO/GGCGGATCTTG/3IAbRQSp/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGCTCAGGTAGTGGTTGTCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eP-Pbr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTAGCGCTGCATCCCATATC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZahr et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56-FAM/CCATGTGAA/ZEN/CCGGTGAC/3IABkFQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeora et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGTTTCGGCTAGGATGGTTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZahr et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eP-Xtt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAAGCCTGACGAGATGGCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFu et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/56-FAM/AGAAATCCA/ZEN/GGGCCATCGTC/3IABkFQ/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGCCTACGCCGGAATACCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eP-Xtu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTCGCTGCTCAGTTGGGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/5HEX/CAAACGGAC/ZEN/TCACTTCGCC/3IABkFQ/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTTCCGGTCGCCACACTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eP-Lb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAAGAATGGCAAAATCACAGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFu et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/56-FAM/AGGAAGAAG/ZEN/CAGCCATAGGC/3IABkFQ/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGCTCTGCGCGACCTTTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eP-Lm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCCTCACACTCTCGACCCCTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFu et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/5HEX/CACAGCCAT/ZEN/ATCATCCTGCA/3IABkFQ/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCATGTTCTTGAACCGCTAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e1\u003c/sup\u003eF = forward primer; R\u0026thinsp;=\u0026thinsp;reverse primer; P\u0026thinsp;=\u0026thinsp;probe\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDNA extraction from\u003c/b\u003e \u003cb\u003eStagonospora nodorum\u003c/b\u003e \u003cb\u003econidia, soil or plant samples\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDNA extraction from \u003cem\u003eS. nodorum\u003c/em\u003e conidia, soil or plant samples was performed with a Qiacube (Qiagen Canada, Toronto, ON). Depending on the sample types, and the purposes of experiments, three DNA extraction methods were used. In Method-1, DNeasy Plant Pro Kits (Qiagen Canada) were used following the manufacturer\u0026rsquo;s instructions. In Method-2, DNeasy Plant Pro Kits were used, but the tissue lysate generated from the lysing step was aliquoted into three tubes and each tube was subjected to one DNA extraction with the same procedure as in Method-1. In Method-3, DNeasy PowerSoil Pro Kits (Qiagen Canada) were used following the manufacturer\u0026rsquo;s instructions. For each method, the resultant DNA was eluted in 50 \u0026micro;L elution buffer included in the kits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of the usefulness of DPGZL-2023 as a DNA extraction control in qPCR diagnosis\u003c/h2\u003e \u003cp\u003eDNA was extracted from 3.75 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e conidia (100 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e conidia per mL) obtained from strain DPGZL-2023 using Method-1. DNA concentration was measured with a NanoDrop-1000. From the extracted DNA, a set of 10\u0026times; serial dilutions was prepared. Using the dilutions as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. The obtained data were used to generate a qPCR standard curve for P-GFP.\u003c/p\u003e \u003cp\u003eDNA was extracted from five samples of 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e conidia (100 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia per mL) obtained from strain DPGZL-2023 using Method-1. Using the five DNA samples as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. In another analysis, Method-1 was used to extract DNA from 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e DPGZL-2023 conidia (100 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia per mL) and, in a separate extraction, DNA was collected from ten 0.5-cm diameter discs cut from canola leaves. A set of 2\u0026times; serial dilutions was prepared from the canola DNA. Using the DPGZL-2023 DNA mixed with each of the canola DNA dilutions as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. The obtained data from the two analyses were used to evaluate variations in the quantity of DNA between replicates.\u003c/p\u003e \u003cp\u003eCanola leaf discs (0.5-cm diameter) were prepared in batches of 30, six, or three leaf discs, and each batch was spiked with 1.125 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia (30 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e conidia per mL) of DPGZL-2023. DNA was extracted from each of the spiked leaf batch with Method-2, which would generate three DNA samples from each spiked leaf batch. Using the DNA samples as the templates, qPCR analyses were conducted with the primers/probe set P-GFP. The obtained data were used to evaluate whether the tissue lysing step in the DNA extraction process caused DNA quantity variation among replicated DNA extractions.\u003c/p\u003e \u003cp\u003eAutoclaved soil samples and resting spore suspensions of the canola clubroot pathogen \u003cem\u003eP. brassicae\u003c/em\u003e were prepared as described by Zahr et al (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Five 100-mg soil samples were prepared, each of which was spiked with 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e DPGZL-2023 conidia (10 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e conidia per mL) and 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e \u003cem\u003eP. brassicae\u003c/em\u003e resting spores (10 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e resting spores per mL). DNA was extracted from these five samples with Method-3. Using the DNA samples as the templates, duplex qPCR analyses were conducted with the primers/probe sets P-GFP and P-Pbr. The obtained data were used to evaluate the usefulness of DPGZL-2023 as a DNA extraction control in duplex qPCR.\u003c/p\u003e \u003cp\u003eFour canola stem samples (Canola-1 to Canola-4) showing blackleg symptoms were collected from fields in Sturgeon County (Canola-1), Wheatland County (Canola-2 and Canola-3) and St. Paul County (Canola-4) of Alberta. From each sample, a 300-mg subsample was prepared. Each subsample was spiked with 1.125 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e DPGZL-2023 conidia (30 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e). DNA was extracted from the spiked samples with Method-2. Using the DNA samples as the templates, triplex qPCR analyses were conducted with the primers/probe sets P-GFP, P-Lb and P-Lm. The obtained data were used to evaluate the usefulness of DPGZL-2023 as a DNA extraction control in triplex qPCR for the detection of fungal pathogens.\u003c/p\u003e \u003cp\u003eOne wheat and two barley (Barley-1 and Barley-2) samples showing bacterial leaf streak symptoms were collected from alternative fields in the vicinities of Edmonton. From each plant, a leaf sample consisting of six leaf discs (0.5-cm diameter) was prepared. Each leaf sample was spiked with 1.125 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e DPGZL-2023 conidia (30 \u0026micro;L of suspension with a concentration of 3.75 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e). DNA was extracted from the spiked samples with Method-2. Using the DNA samples as the templates, triplex qPCR analyses were conducted with the primers/probe sets P-GFP, P-Xtt and P-Xtu. The obtained data were used to evaluate the usefulness of DPGZL-2023 as a DNA extraction control in triplex qPCR for the detection of bacterial pathogens.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe qPCR standard curve was constructed by regression analysis using the SAS software (version 9.4; SAS Institute, Cary, NC). SAS was also used to evaluate data from each experiment by analysis of variance (ANOVA). Differences between qPCR reactions were assessed with the Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTransformant identification\u003c/h2\u003e \u003cp\u003eThree transformants were selected from one transformation experiment and purified by the single spore method. Hyphae from the three transformants and the three single-spore isolates showed similar GFP signals under the microscope (data not shown). The presence of the GFP coding sequence in the three single-spore isolates was confirmed by PCR using the primer pair P-Seq (data not shown). One single spore isolate named DPGZL-2023 was used in further studies. DPGZL-2023 was deposited to the Alberta Plant Health Lab culture collection and is available free to other researchers upon request.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGFP activity and pathogenicity of DPGZL-2023\u003c/h2\u003e \u003cp\u003eUnder the Dark Reader Transilluminator, green florescence was observed from the colony of DPGZL-2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Under the microscope, green florescence was observed from the conidia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) \u003cem\u003ein vitro\u003c/em\u003e and conidia and hyphae \u003cem\u003ein planta\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). On wheat cultivar Harvest, DPGZL-2023 had similar pathogenicity as the wild type (data not shown).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eqPCR analysis on the repeatability of the primers/probe set P-GFP\u003c/h2\u003e \u003cp\u003eSequencing the PCR product of P-Seq from the vector DNA resulted in a 531-bp clean sequence, identical to nucleotides (nt) 515\u0026ndash;1045 of the cloning vector pCEBN-GFP (GenBank accession number MN781141). Based on this sequence, the qPCR primers/probe set P-GFP was designed. A qPCR standard curve was constructed for P-GFP based on the Cq values from a serial dilution set of DPGZL-2023 DNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The efficiency of P-GFP was 0.97. The standard curve provided a reference on how many DPGZL-2023 conidia should be used to spike a sample to be tested for pathogens.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDNA was extracted from five replicates of 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e DPGZL-2023 conidia. qPCR was conducted on these five DNA samples using P-GFP. Differences in the Cq values were found among these five replicates (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This result indicated that variation or a part of the variation in Cq values among replicates was predetermined in the stages before qPCR set up.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eqPCR analysis of DNA from the \u003cem\u003eStagonospora nodorum\u003c/em\u003e strain DPGZL-2023\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRep\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCq\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.53a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.47a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.33b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.21c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.11d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003eDNA was extracted from five replicates of conidia samples with each sample containing 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e conidia. The extracted DNA from each conidia sample was dissolved in 50 \u0026micro;L water.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e2\u003c/sup\u003eThe quantification cycle (Cq) values of three technical replicates for each DNA sample. Two \u0026micro;L of DNA was used in each 20-\u0026micro;L qPCR reaction, which was equivalent to the DNA from 1.5 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e conidia.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e3\u003c/sup\u003eSD = standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e4\u003c/sup\u003eMeans followed by the same letter do not differ based on Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe stages before qPCR included sample preparation and DNA extraction. To verify that DNA extraction was the factor causing the Cq variation among DNA samples, DPGZL-2023 DNA was mixed with different aliquots of canola DNA and then the mixtures were used as templates in qPCR analysis using P-GFP. No Cq difference was observed among the DNA samples (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This result indicated that the DNA extraction, rather than sample preparation, was responsible for the observed Cq differences among DNA samples.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eqPCR analysis of DNA samples containing a mixture of \u003cem\u003eStagonospora nodorum\u003c/em\u003e DNA and canola DNA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSno\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanola\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eCq\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSD\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.39a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/2\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.26a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/4\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.30a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/8\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.25a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/16\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.37a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026times;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.26a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003eDNA was extracted from 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e conidia of the \u003cem\u003eS. nodorum\u003c/em\u003e strain DPGZL-2023 and ten 0.5-cm diameter leaf discs of canola. Both DNA samples were dissolved in 50 \u0026micro;L water. A set of two-time serial dilutions were prepared from the canola DNA.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e2\u003c/sup\u003eThe quantification cycle (Cq) values of three technical replicates for each DNA sample. The template in each 20-\u0026micro;L qPCR reaction consisted of 2 \u0026micro;L of the Sno DNA and 2 \u0026micro;L of each of the serial dilutions of canola DNA.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e3\u003c/sup\u003eSD = standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e4\u003c/sup\u003eMeans followed by the same letter do not differ based on Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe first step of DNA extraction using the Qiagen kits is sample lysing. After centrifugation of the lysate, the supernatant was transferred into a new tube for the subsequent DNA extraction. To evaluate whether the sample lysing step caused the Cq variation among DNA samples, DNA was extracted from aliquots of lysates from a mixture consisting of DPGZL-2023 conidia and canola leaves. qPCR analysis using P-GFP indicated that there was no Cq variation among DNA samples extracted from aliquots of the same lysate, although variation was still present among DNA samples extracted from different lysate preparations (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This result indicated that the sample lysing step in DNA extraction caused the Cq value variation among DNA samples.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eqPCR analysis of DNA extracted from samples consisting of \u003cem\u003eStagonospora nodorum\u003c/em\u003e conidia and canola leaves\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDNA\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRep\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eCq\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSD\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.31b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.19b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.28b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.78a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.70a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.76a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.64a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.81a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.73a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003eCanola leaf discs (0.5-cm diameter) were prepared. Thirty (A), six (B) or three (C) leaf discs were spiked with 1.125 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia of the \u003cem\u003eS. nodorum\u003c/em\u003e strain DPGZL-2023. After the tissue homogenization step of DNA extraction, the supernatant of A, B or C was aliquoted into three tubes (Rep 1\u0026ndash;3). DNA was extracted from each tube and dissolved in 50 \u0026micro;L water.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e2\u003c/sup\u003eThe quantification cycle (Cq) values of three technical replicates for each DNA sample. Two \u0026micro;L of DNA was used in each 20-\u0026micro;L qPCR reaction.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e3\u003c/sup\u003eSD = standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e4\u003c/sup\u003eMeans followed by the same letter do not differ based on Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eqPCR analysis on the usefulness of DPGZL-2023 as DNA extraction control in plant disease diagnosis\u003c/h2\u003e \u003cp\u003eThe usefulness of DPGZL-2023 as a DNA extraction control was tested in qPCR diagnosis of the clubroot pathogen \u003cem\u003eP. brassicae\u003c/em\u003e. DNA was extracted from mixtures of DPGZL-2023 conidia and clubroot resting spores and used in duplex qPCR with the primers/probe sets P-GFP and P-Pbr. Variations in the Cq values of P-GFP, as well as P-Pbr, were observed among the replicates (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Nevertheless, the trend of P-GFP Cq fluctuation among replicates was identical to that of P-Pbr, suggesting that the Cq values of P-GFP could be used as a DNA extraction control in diagnosis of clubroot and the control function could be either qualitative or quantitative.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDuplex qPCR analysis of DNA extracted from soil samples containing conidia of \u003cem\u003eStagonospora nodorum\u003c/em\u003e strain DPGZL-2023 (P-GFP) and resting spores of \u003cem\u003ePlasmodiophora brassicae\u003c/em\u003e (P-Pbr)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eP-GFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003eP-Pbr\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRep\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCq\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eCq\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSD\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eMean\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.51a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.20a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.36b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.03b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.35bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.05b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.32bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.98b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.27c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.88c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e1\u003c/sup\u003eDNA was extracted from five replicates with each replicate consisting of 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e Sno conidia and 3.75 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e Pbr resting spores. DNA from each replicate was dissolved in 50 \u0026micro;L water.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e2\u003c/sup\u003eThe quantification cycle (Cq) values of three technical replicates for each DNA sample. Two \u0026micro;L of DNA was used in each 20-\u0026micro;L duplex qPCR reaction.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e3\u003c/sup\u003eSD = standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e4\u003c/sup\u003eMeans followed by the same letter do not differ based on Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe usefulness of DPGZL-2023 as a DNA extraction control was also tested in qPCR diagnosis of the two canola blackleg pathogens \u003cem\u003eL. biglobosa\u003c/em\u003e and \u003cem\u003eL. maculans\u003c/em\u003e. DNA was extracted from four symptomatic canola stem samples spiked with DPGZL-2023 conidia and used in triplex qPCR with the primers/probe sets P-GFP, P-Lb and P-Lm. \u003cem\u003eLeptosphaeria maculans\u003c/em\u003e was detected from the sample Canola-1 and \u003cem\u003eL. biglobosa\u003c/em\u003e was detected from Canola-2; Both \u003cem\u003eL. maculans\u003c/em\u003e and \u003cem\u003eL. biglobosa\u003c/em\u003e were detected from Canola-3 and Canola-4 (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Among the three DNA replicates from each lysate, no Cq difference was observed for all the three primers/probe sets. However, for each of the three primers/probe sets, Cq differences were observed among plant samples. While such differences of P-Lb and P-Lm Cq values could be primarily due to different infection levels in the stems, the difference of P-GFP values was due to the lysing process of DNA extraction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTriplex qPCR analysis of DNA extracted from canola stem samples for characterization of the blackleg pathogens \u003cem\u003eLeptosphaeria biglobosa\u003c/em\u003e and \u003cem\u003eL. maculans\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eP-GFP\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eP-Lb\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eP-Lm\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRep\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCanola-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.98cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.76ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.04c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.78ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.03c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.81a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCanola-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.85ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.30a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.97a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.51a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.75ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.31a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCanola-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.62b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.60bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.62bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.80ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.69b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.71abc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.66b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.63b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.59c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCanola-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.68e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.28c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.06d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.77de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.40bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.12d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.77de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.27c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.05d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e1\u003c/sup\u003eA 300-mg subsample from each stem sample was prepared. Each subsample was spiked with 1.125 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia of the \u003cem\u003eS. nodorum\u003c/em\u003e strain DPGZL-2023. After the tissue homogenization step of DNA extraction, the supernatant of each subsample was aliquoted into three tubes (Rep 1\u0026ndash;3). DNA was extracted from each tube and dissolved in 50 \u0026micro;L water.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e2\u003c/sup\u003eThe mean quantification cycle (Cq) values of three technical replicates for each DNA sample. Two \u0026micro;L of DNA was used in each 20-\u0026micro;L qPCR reaction. SD\u0026thinsp;=\u0026thinsp;standard deviation. Means followed by the same letter do not differ based on Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe usefulness of DPGZL-2023 as a DNA extraction control was further tested in qPCR diagnosis of the two wheat bacterial leaf streak (BLS) pathogens Xtt and Xtu. DNA was extracted from symptomatic barley and wheat leaves spiked with DPGZL-2023 conidia and used in triplex qPCR with the primers/probe sets P-GFP, P-Xtt and P-Xtu. Xtu was detected from the wheat sample; Xtt was detected from one barley sample; Both Xtt and Xtu were detected from the other barley sample (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Among the three DNA replicates from each lysate, no Cq difference was observed for all the three primers/probe sets. However, for each of the three primers/probe sets, Cq differences were observed among plant samples. Again, while such differences of P-Xtt and P-Xtu Cq values could be primarily due to different infection levels in the leaves, the difference of P-GFP values was due to the lysing process of DNA extraction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTriplex qPCR analysis of DNA extracted from wheat or barley samples for characterization of the bacterial leaf streak pathovars Xtt and Xtu in wheat and barley\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eP-GFP\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eP-Xtt\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eP-Xtu\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRep\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eWheat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.22b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.15b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.99b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.19b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.97b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBarley 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.43c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.34b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.60a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.42c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.38b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.61a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.46c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.45b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.79a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBarley 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.48a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.17a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.46a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.08a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.49a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.28a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e1\u003c/sup\u003eSix leaf discs (0.5-cm diameter) from each plant sample were prepared. Each leaf sample was spiked with 1.125 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e conidia of the \u003cem\u003eS. nodorum\u003c/em\u003e strain DPGZL-2023. After the tissue homogenization step of DNA extraction, the supernatant of each plant sample was aliquoted into three tubes (Rep 1\u0026ndash;3). DNA was extracted from each tube and dissolved in 50 \u0026micro;L water.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e2\u003c/sup\u003eThe mean quantification cycle (Cq) values of three technical replicates for each DNA sample. Two \u0026micro;L of DNA was used in each 20-\u0026micro;L qPCR reaction. SD\u0026thinsp;=\u0026thinsp;standard deviation. Means followed by the same letter do not differ based on Tukey's multiple comparison test at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGFP has been used as a reporter marker because it provides a visual means to identify genetically engineered cells (Lippincott-Schwartz and Patterson \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The wild-type GFP has a major absorption maximum at 397 nm and a minor excitation peak at 475 nm (Yang et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Modified forms of GFP, including the SGFP used in the current study, have a \u0026ldquo;red shift\u0026rdquo; from excitation maxima of 395 and 470 nm to a maximum of 488 nm (Lorang et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), which enables the GFP activity to be detected with a blue-light Dark Reader Transilluminator. The DPGZL-2023 strain generated in this study can produce a strong GFP signal that could be early detected \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein planta.\u003c/em\u003e Having a similar pathogenicity as the wild-type, DPGZL-2023 may be useful as a tool to study the pathogenicity of \u003cem\u003eS. nodorum\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn plant diagnostics labs, negative results are commonly obtained from tested samples. A negative PCR results can be explained by three conditions: 1) absence of the target (true negative), 2) failure of the PCR protocol to amplify the target (false negative), or 3) poor DNA extraction (false negative). All diagnostic tests should include at least one positive control and one negative control. Generally, the positive control used in PCR tests is \u0026ldquo;control\u0026rdquo; of the PCR/qPCR system rather than the template DNA. Such positive controls can be DNA from the target organism or synthesized DNA containing the target sequence. Adding this control DNA after extraction allows for monitoring of inhibition within the assay and rule out false negatives due to a failure of the PCR reaction, but cannot detect a false negative due to a DNA extraction error. The method described herein can be used as a second positive control, or standard, to report the success or efficiency of DNA extraction. Using both an internal positive control, and a DNA extraction control, allows one to rule out both causes of a false negative so that true negative results can be confirmed. In our hands, the control agent has been easy to prepare and the measurement of DNA extraction reported with a high accuracy.\u003c/p\u003e \u003cp\u003eThe GFP-labeled \u003cem\u003eS. nodorum\u003c/em\u003e strain described here has advantages for use as such a DNA extraction control. 1) This fungus can rapidly produce large numbers of conidia on commonly used agar media within 1\u0026ndash;2 weeks, and the conidia are easily purified, i.e. without mycelia, 2) The conidia can be easily quantified with a hemocytometer due to the size, the shape and the color of the conidia and 3) the DNA sequence of the GFP gene (from jelly fish) is unlikely present in plants and plant-associated microorganisms including plant pathogens. Other evidences for the user-friendly nature of GFP-labeled \u003cem\u003eS. nodorum\u003c/em\u003e include: 1) \u003cem\u003eS. nodorum\u003c/em\u003e can be easily transformed for gene insertion (Feng et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; this study) and 2) All the DPGZL-2003 conidia used in this study represented only a portion of conidia produced on one 10-cm petri dish (2 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e conidia per petri dish).\u003c/p\u003e \u003cp\u003eThe DPGZL-2023 strain and the primers/probe set P-GFP developed in the current study are especially useful for disease diagnosis from soil samples. The amount of DNA extracted from soil samples could have a large differences ranging from trace amounts, unmeasurable with a spectrophotometer, to large amounts. This can be due to inhibition of DNA accessibility or survival in soil and also influenced by the amount of other non-target organisms present. For quantitative tests, such as population dynamic studies on soilborne pathogens, a DNA extraction control is essential so that fair comparisons and conclusions can be made. This was demonstrated in the current study. However, a preliminary literature search indicated that a control or standard for DNA extraction has never attracted attention or gained favor.\u003c/p\u003e \u003cp\u003eDNA extraction efficiency affecting the accuracy of plant disease diagnosis or pathogen quantification has been studied previously (Yang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and experimentally confirmed by the current study. In the current study, a Qiacube was used for all DNA extraction which would increase the consistency of DNA yield across different samples compared to a human technician manually employing a DNA extraction kit. However, variation on DNA yield was still present even using the Qiacube. This observation further highlights that caution should always be exercised when interpreting qPCR data if no DNA extraction control was included.\u003c/p\u003e \u003cp\u003eIn conclusion, the current study emphasized the importance of including a DNA extraction control in qPCR-based plant disease diagnosis. The development of a DNA extraction control system was described, and demonstrated in multiple examples of sample types, and qPCR systems. This system is now a standard used in detection or evaluation of all diagnostic and disease survey/monitoring samples in the Alberta Plant Health Lab. We recommend that other diagnostic labs also adopt this standard in their qPCR diagnostics, population studies and surveillance/monitoring sample evaluations, and are willing to provide the DPGZL-2023 strain to others free of charge, upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlvandi H, Taghavi SM, Khojasteh M, Rahimi T, Dutrieux C, Taghouti G, Jacques MA, Portier P, Osdaghi E (2023) Pathovar-specific PCR method for detection and identification of \u003cem\u003eXanthomonas translucens\u003c/em\u003e pv. \u003cem\u003eundulosa\u003c/em\u003e. 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Phytopathology 111:1743\u0026ndash;1750. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PHYTO-09-20-0415-R\u003c/span\u003e\u003cspan address=\"10.1094/PHYTO-09-20-0415-R\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clubroot, Blackleg, Bacterial leaf streak, Xanthomonas translucens pv. undulosa, Xtt, Xtu","lastPublishedDoi":"10.21203/rs.3.rs-3922075/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3922075/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA \u003cem\u003eStagonospora nodorum\u003c/em\u003e strain named DPGZL-2023 was created by transferring a green florescent protein (GFP) gene into the genome of the \u003cem\u003eS. nodorum\u003c/em\u003e strain Sn15. DPGZL-2023 showed a similar pathogenicity as Sn15 but carried a strong GFP activity. A qPCR primers/probe set named P-GFP, targeting the GFP sequence, was designed. Using P-GFP, qPCR analysis was conducted on DNA extracted from replicated samples of DPGZL-2023 conidia, and confirmed that DPGZL-2023 could be used to characterize the variation in replicated DNA extractions. Conidia of DPGZL-2023 were used to spike soil samples inoculated with the canola clubroot pathogen \u003cem\u003ePlasmodiophora brassicae\u003c/em\u003e, canola stem samples infected with the blackleg pathogens \u003cem\u003eLeptosphaeria biglobosa\u003c/em\u003e and/or \u003cem\u003eL. maculans\u003c/em\u003e and wheat/barley samples infected with \u003cem\u003eXanthomonas translucens\u003c/em\u003e pv. \u003cem\u003etranslucens\u003c/em\u003e (Xtt) or \u003cem\u003eX. translucens\u003c/em\u003e pv. \u003cem\u003eundulosa\u003c/em\u003e (Xtu). Duplex qPCR using P-GFP and a primers/probe set specific to \u003cem\u003eP. brassicae\u003c/em\u003e, triplex qPCR using P-GFP and primers/probe sets specific to \u003cem\u003eL. biglobosa\u003c/em\u003e and \u003cem\u003eL. maculans\u003c/em\u003e, and triplex qPCR using P-GFP and primers/probe sets specific to Xtt and Xtu were conducted. The results indicated that DPGZL-2023 could be used as a standard for DNA extraction efficiency in qPCR-based plant disease diagnosis. Adding DPGZL-2023 conidia to plant or soil samples prior to DNA extraction, and subsequent use of the P-GFP detection control, provided an added control that could distinguish truly negative from false-negative qPCR results.\u003c/p\u003e","manuscriptTitle":"Using a GFP-labeled Stagonospora nodorum strain as a DNA extraction efficiency standard in plant disease diagnosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-07 21:51:06","doi":"10.21203/rs.3.rs-3922075/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1960b1bf-c685-4f9c-bf24-515fb7d73e85","owner":[],"postedDate":"February 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-06T00:33:38+00:00","versionOfRecord":{"articleIdentity":"rs-3922075","link":"https://doi.org/10.1016/j.cropro.2024.106789","journal":{"identity":"crop-protection","isVorOnly":true,"title":"Crop Protection"},"publishedOn":"2024-06-01 00:33:38","publishedOnDateReadable":"June 1st, 2024"},"versionCreatedAt":"2024-02-07 21:51:06","video":"","vorDoi":"10.1016/j.cropro.2024.106789","vorDoiUrl":"https://doi.org/10.1016/j.cropro.2024.106789","workflowStages":[]},"version":"v1","identity":"rs-3922075","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3922075","identity":"rs-3922075","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}