A rapid molecular diagnostic tool to discriminate alleles of avirulence genes and haplotypes of 
INTRODUCTION Soybean ( Glycine max ) seeds provide protein and oil for animal feed and human consumption. Soybean is the fourth largest field crop in the world and meets 60% of global vegetable oil demand (USDA, ). Worldwide production reached 350 million tonnes in 2018 (FAOStat, ) but diseases caused by fungal and oomycete pathogens remain a major limitation for soybean production. Among them, Phytophthora stem and root rot (PRR), caused by the oomycete soilborne pathogen Phytophthora sojae , is particularly devastating because it can attack soybean plants at all growth stages (Dorrance et al., ; Tyler, ). The development of PRR is influenced by several factors, including compactness of soil, favourable temperature, inoculum density and planting susceptible cultivars. Poor soil drainage and excessive soil moisture create a favourable environment for the pathogen spread in the soil. The optimum temperature for disease development is 25–30°C. Germination and the spread of P. sojae are limited outside the optimum temperature range. P. sojae survives in the soil for extended periods in the form of thick‐walled resting structures called oospores, which serve as the primary source of inoculum. Under favourable conditions the oospores germinate and infect susceptible soybean plants. An effective way to reduce PRR damage is to plant soybean cultivars with genes conferring resistance to P. sojae ( Rps ). These genes encode proteins containing nucleotide‐binding site and leucine‐rich repeat (NLR) motifs (Caplan et al., ; Gao et al., ; Gao & Bhattacharyya, ; Sandhu et al., ). Avirulence ( Avr ) genes of P. sojae encode effector proteins that are expressed only during infection, and most of them contain RxLR and DEER domains believed to be required for translocation (Dou et al., , ; Whisson et al., ). When a soybean Rps recognizes the corresponding Avr from P. sojae , plant defence reactions are triggered, resulting in disease resistance (Madina et al., ). Overexploitation of single Rps genes in the field exerts a strong selection pressure against the avirulent isolates, which in turn enrich the selection of genetic variants of Avr genes or its regulatory elements favouring virulence (Arsenault‐Labrecque et al., ). Genetic modifications such as insertion, deletion and substitution in the promoter region or in the coding sequence of Avr genes allow the pathogen to evade host recognition and infect the plant (Ali et al., ; Arsenault‐Labrecque et al., ; Iida et al., ; Qutob et al., ; Rep et al., ). The estimated lifespan of newly introduced Rps genes ranges from 8 to 20 years. The effectiveness of Rps1a lasted for 40 years, while that of Rps1c and 1k was less than 20 years (Yan & Nelson, ). The virulence profile refers to the combination of virulence genes exhibited by a P. sojae isolate. The virulence profile can vary among different isolates and is typically characterized by its ability to overcome Rps in soybean plants. The virulence profiles of P. sojae evolve over time as the pathogen adapts to selective pressure imposed by resistant soybean cultivars. Diversification of Avr genes in P. sojae has led to increased virulence profiles and limits the effectiveness of Rps genes in soybean (Tremblay et al., ). This information is crucial for soybean breeders and pathologists to develop new resistant varieties by identifying and deploying Rps genes that can effectively counter the prevalent virulence factors in P. sojae populations. To date, more than 33 Rps genes/alleles have been reported in soybean while six of them ( Rps1a , 1b , 1c , 1k , 3a and 6 ) have been introgressed into commercial soybean varieties (Dorrance, ; Jiang et al., ). Most of the Avr genes in P. sojae are located in repeat‐rich regions, have high levels of sequence homology (e.g., Avr1a and Avr1c ) and vary in copy numbers (e.g., Avr1a and Avr3a ), which makes it challenging to develop sequence‐based diagnostic markers to detect all haplotypes. To identify and characterize rapidly evolving P. sojae isolates, Arsenault‐Labrecque et al.  defined specific haplotypes for seven Avr genes ( 1a , 1b , 1c , 1d , 1k , 3a and 6 ) using comparative whole‐genome analysis of 31 P. sojae isolates. Further validation by hydroponic assay showed that each identified haplotype corresponded to a distinct virulence profile (Arsenault‐Labrecque et al., ). Based on these results, Dussault‐Benoit et al.  identified unique sequences and developed a diagnostic multiplex PCR tool to detect the presence of alleles conferring an avirulent phenotype for isolates containing seven Avr genes ( 1a , 1b , 1c , 1d , 1k , 3a and 6 ). Quantitative PCR monitors the amount of PCR product in real time by using intercalating dyes (e.g., SYBR Green). The disadvantages of using intercalating dyes are that they nonspecifically bind to off‐target DNA, primer dimers, and can inhibit PCR processes, resulting in the generation of false‐positive signals, and reduced specificity and sensitivity of the assay (Navarro et al., ). Using target‐specific TaqMan probes can overcome these limitations, but they are expensive. High‐resolution melting curve (HRM) analysis is a post‐PCR method that detects and differentiates nucleic acid sequences based on their melting behaviour, which depends on the length and the transition to complement (T‐C) ratio of the target. Intercalating fluorescent dyes exhibit fluorescence only when bound to double‐stranded (ds)DNA; during the melting process, where dsDNA dissociates into single strands, the fluorescence level decreases (Bezdicek et al., ; Herrmann et al., ; Montgomery et al., ; Tong & Giffard, ). Nonsaturating dyes like SYBR Green inhibit polymerase activity at higher concentration and rebind on free sites during the melting process. However, saturating dyes such as EvaGreen, LcGreen and SYTO9 do not inhibit DNA polymerase even at higher concentrations and hence can be used at saturation (Duyvejonck et al., ). The sensitivity of the HRM method has significantly increased due to the development of “release‐on‐demand dyes” such as EvaGreen, improved instrumentation for detecting melt behaviour and advanced software for post‐HRM analysis. HRM can now reliably detect sequence variations, including single‐nucleotide polymorphisms (SNPs) and insertions/deletions (indels) (Twist et al., ). HRM analysis has been successfully used in clinical medicine (Bezdicek et al., ; Garritano et al., ), the detection and differentiation of viruses (Gelaye et al., ), the detection and genotyping of plant‐pathogenic Fusarium spp. (Brandfass & Karlovsky, ; Ganopoulos et al., ; Schiwek et al., ), genotyping the avirulence AvrLm4‐7 gene of Leptosphaeria maculans (Carpezat et al., ), genotyping isolates of apple scab pathogen (Chatzidimopoulos et al., ), detection and differentiation of strawberry crown rot and Pestalotia leaf spot pathogens (Rebello et al., ; Wang et al., ), and, recently, identification of mutants generated by CRISPR‐Cas9 (Rocafort et al., ; Santhanam et al., ). Although, HRM has been a widely used tool to study genetic variations, it has yet to be exploited to study variations in pathogen effectors that are required for successful colonization or recognition mediated by resistance gene products. In this study, we developed a sensitive and robust HRM assay to discriminate all haplotypes of six different Avr genes ( Avr1b , 1c , 1d , 1k , 3a and 6 ) in P. sojae isolates that confer virulence/avirulence in soybean cultivars containing the corresponding Rps gene. In the context of the P. sojae– soybean interaction, these results offer a powerful tool to better manage the disease through an educated selection of Rps genes resistant to P. sojae haplotypes present in the field.   RESULTS 2.1 Variant detection by HRM from known genotypes To develop the initial proof of concept, four different allelic variants of Avr6 (wt, T218G, G214X and 214‐5X) were synthesized. HRM analysis was performed on the amplicon of four different genotypes of Avr6 : a wild type (wt), a transversion mutation of T to G at the 218th nucleotide from the start codon (T218G), a deletion of G at the 214th nucleotide from the start codon (G214X) and, finally, deletion of five nucleotides from 214th to 218th nucleotides from the start codon (214‐5X) (Figure ). As shown in Figure , based on the fluorescence melting‐curve analysis, each genotype exhibited a unique and distinct curve pattern compared to the wild type (Figure ). The differences were easily visualized even if a single nucleotide separated the amplicons. 2.2 HRM analysis of six Avr genes with known genotypes To ascertain that HRM was suitable for efficient genotyping of P. sojae isolates, the sensitivity of the assay for detection of different types of DNA polymorphisms (Figures , ) was tested using six common Avr genes in 12 P. sojae isolates previously characterized phenotypically and genotypically (Arsenault‐Labrecque et al., ). These 12 isolates carried either avirulent or virulent alleles for each Avr gene (Table ). In the case of Avr3a and Avr6 with only two haplotypes, a virulent and an avirulent form, melt curve analysis clearly formed two separate curves representing the presence of the avirulence (haplotype A) and virulence (haplotype B) allele in 12 P. sojae isolates (Figure ). As for Avr1b and Avr1k , which are often present in tandem in isolates, all 12 tested isolates had either two avirulent forms (haplotypes A and B) or one virulent form (haplotype C). HRM analysis not only predicted the pathotypes but also distinguished all three haplotypes with unique curves (Figure ). In the case of Avr1d , previously reported to have three haplotypes (Arsenault‐Labrecque et al., ), A, B and C, the results clearly separated the expected avirulent (haplotypes A and B) and virulent forms (haplotype C; Figure ). Interestingly, the virulent isolate UL_082, which had exhibited a few base pair differences with other virulent isolates in Arsenault‐Labrecque et al. , exhibited a unique curve from the rest of the isolates consistently (Figure ). Sequencing of the amplicon confirmed the reported differences (Figure ). The coding sequence of Avr1c was by far the most complex, with five different haplotypes, two avirulent and three virulent ones, including an 8–10 kb deletion that could not be amplified. As a result, HRM analysis effectively predicted DNA sequence polymorphisms in Avr1c and produced a unique melt curve for each haplotype (Figure ). Expectedly, isolate UL_296, containing the large deletion and referred to as haplotype E, did not amplify (Figure ). 2.3 Predicting P. sojae pathotypes from uncharacterized isolates After successfully establishing a perfect correlation between genotypes determined by the HRM method and phenotypes with previously characterized isolates, we applied the HRM method to predict the pathotype of unknown isolates collected in the field. For this purpose, we selected 12 uncharacterized isolates that were compared for six Avr genes to four control isolates described above. HRM analysis of Avr3a and Avr6 in 12 previously uncharacterized isolates exhibited two distinguishing melt curves similar to the control isolates, corresponding to either a virulent or avirulent pathotype. Overall, 11/12 were avirulent towards Avr3a and 11/12 towards Avr6 (Figure ). For Avr1b and Avr1k , both are known to contain three haplotypes, A and B (avirulent) and C (virulent). When HRM analysis was performed with the 12 previously uncharacterized isolates, they all exhibited distinguishable melt curves identical to the control isolates for each of the pathotypes as well as haplotypes (Figure ). In the end, six isolates were avirulent and, expectedly, isolates avirulent towards Avr1b were also avirulent towards Avr1k . In the case of Avr1d displaying three possible haplotypes, only two haplotypes were found in the isolates tested and all but two carried the virulent allele (Figure ). As mentioned previously, Avr1c has five different haplotypes of which four are detectable (A–D) owing to a large deletion in the region of the fifth haplotype (E). HRM analysis on the 12 field isolates clearly detected the presence of four haplotypes, and the curves were similar to curves generated by controls (Figure ). None of the field isolates carried haplotype E. To validate the HRM‐based pathotype prediction, all 12 isolates were phenotyped using the hydroponic assay. As shown in Figures and , phenotyping results are presented for all isolates against all six Rps genes (Figures and ). In all cases, the phenotypic response in terms of virulence or avirulence matched the predicted pathotyping by the HRM based on the haplotypes. For Avr1b , isolates UL_082 (virulent control), UL_820, UL_829, UL_848, UL_851, UL_860 and UL_865 were predicted to be virulent by HRM analysis. When the hydroponic assay was performed on soybean differential Rps1b , these isolates were virulent and the results matched perfectly with the HRM prediction (Figure ). Similarly, HRM‐based assay was able to predict the pathotype of Avr1c (Figure ), Avr1d (Figure ), Avr1k (Figure ), Avr3a (Figure ), and Avr6 (Figure ) in all 12 isolates with 100% accuracy.   Variant detection by HRM from known genotypes To develop the initial proof of concept, four different allelic variants of Avr6 (wt, T218G, G214X and 214‐5X) were synthesized. HRM analysis was performed on the amplicon of four different genotypes of Avr6 : a wild type (wt), a transversion mutation of T to G at the 218th nucleotide from the start codon (T218G), a deletion of G at the 214th nucleotide from the start codon (G214X) and, finally, deletion of five nucleotides from 214th to 218th nucleotides from the start codon (214‐5X) (Figure ). As shown in Figure , based on the fluorescence melting‐curve analysis, each genotype exhibited a unique and distinct curve pattern compared to the wild type (Figure ). The differences were easily visualized even if a single nucleotide separated the amplicons.   HRM analysis of six Avr genes with known genotypes To ascertain that HRM was suitable for efficient genotyping of P. sojae isolates, the sensitivity of the assay for detection of different types of DNA polymorphisms (Figures , ) was tested using six common Avr genes in 12 P. sojae isolates previously characterized phenotypically and genotypically (Arsenault‐Labrecque et al., ). These 12 isolates carried either avirulent or virulent alleles for each Avr gene (Table ). In the case of Avr3a and Avr6 with only two haplotypes, a virulent and an avirulent form, melt curve analysis clearly formed two separate curves representing the presence of the avirulence (haplotype A) and virulence (haplotype B) allele in 12 P. sojae isolates (Figure ). As for Avr1b and Avr1k , which are often present in tandem in isolates, all 12 tested isolates had either two avirulent forms (haplotypes A and B) or one virulent form (haplotype C). HRM analysis not only predicted the pathotypes but also distinguished all three haplotypes with unique curves (Figure ). In the case of Avr1d , previously reported to have three haplotypes (Arsenault‐Labrecque et al., ), A, B and C, the results clearly separated the expected avirulent (haplotypes A and B) and virulent forms (haplotype C; Figure ). Interestingly, the virulent isolate UL_082, which had exhibited a few base pair differences with other virulent isolates in Arsenault‐Labrecque et al. , exhibited a unique curve from the rest of the isolates consistently (Figure ). Sequencing of the amplicon confirmed the reported differences (Figure ). The coding sequence of Avr1c was by far the most complex, with five different haplotypes, two avirulent and three virulent ones, including an 8–10 kb deletion that could not be amplified. As a result, HRM analysis effectively predicted DNA sequence polymorphisms in Avr1c and produced a unique melt curve for each haplotype (Figure ). Expectedly, isolate UL_296, containing the large deletion and referred to as haplotype E, did not amplify (Figure ).   Predicting P. sojae pathotypes from uncharacterized isolates After successfully establishing a perfect correlation between genotypes determined by the HRM method and phenotypes with previously characterized isolates, we applied the HRM method to predict the pathotype of unknown isolates collected in the field. For this purpose, we selected 12 uncharacterized isolates that were compared for six Avr genes to four control isolates described above. HRM analysis of Avr3a and Avr6 in 12 previously uncharacterized isolates exhibited two distinguishing melt curves similar to the control isolates, corresponding to either a virulent or avirulent pathotype. Overall, 11/12 were avirulent towards Avr3a and 11/12 towards Avr6 (Figure ). For Avr1b and Avr1k , both are known to contain three haplotypes, A and B (avirulent) and C (virulent). When HRM analysis was performed with the 12 previously uncharacterized isolates, they all exhibited distinguishable melt curves identical to the control isolates for each of the pathotypes as well as haplotypes (Figure ). In the end, six isolates were avirulent and, expectedly, isolates avirulent towards Avr1b were also avirulent towards Avr1k . In the case of Avr1d displaying three possible haplotypes, only two haplotypes were found in the isolates tested and all but two carried the virulent allele (Figure ). As mentioned previously, Avr1c has five different haplotypes of which four are detectable (A–D) owing to a large deletion in the region of the fifth haplotype (E). HRM analysis on the 12 field isolates clearly detected the presence of four haplotypes, and the curves were similar to curves generated by controls (Figure ). None of the field isolates carried haplotype E. To validate the HRM‐based pathotype prediction, all 12 isolates were phenotyped using the hydroponic assay. As shown in Figures and , phenotyping results are presented for all isolates against all six Rps genes (Figures and ). In all cases, the phenotypic response in terms of virulence or avirulence matched the predicted pathotyping by the HRM based on the haplotypes. For Avr1b , isolates UL_082 (virulent control), UL_820, UL_829, UL_848, UL_851, UL_860 and UL_865 were predicted to be virulent by HRM analysis. When the hydroponic assay was performed on soybean differential Rps1b , these isolates were virulent and the results matched perfectly with the HRM prediction (Figure ). Similarly, HRM‐based assay was able to predict the pathotype of Avr1c (Figure ), Avr1d (Figure ), Avr1k (Figure ), Avr3a (Figure ), and Avr6 (Figure ) in all 12 isolates with 100% accuracy.   DISCUSSION Several recent studies have highlighted growing concerns about P. sojae evolving pathotypes that are steadily overcoming commercial Rps genes around the world (Dorrance, ; Tremblay et al., ). There is a general consensus that Rps1a and 1c have become mostly inefficient while Rps1k is becoming obsolete rapidly (McCoy et al., ). For these reasons, there is an increasing need to properly and rapidly define the pathotype of P. sojae isolates in order to deploy the proper Rps genes. Historically, the virulence profile of P. sojae has been determined following extraction of isolates from soil or plant samples followed by inoculation on soybean differentials containing the Rps genes of interest through hypocotyl inoculation or other bioassays. This approach is fastidious, time‐consuming and prone to phenotyping errors (Lebreton et al., ; Xue et al., ). The aim of this study was to develop a simple and rapid HRM assay that would allow discrimination between virulence and avirulence alleles of P. sojae isolates as a rapid and precise predictive tool of their pathotype. Indeed, by rapidly identifying pathotypes of P. sojae isolates present in soybean fields, soybean cultivars containing the proper Rps can be recommended. In this work, we report the successful differentiation of P. sojae haplotypes of six different Avr genes ( 1b , 1c , 1d , 1k , 3a and 6 ) by HRM analysis to precisely predict the pathotypes of P. sojae isolates. A number of reports have exploited HRM‐based identification of genetic variants in clinical trials (Bezdicek et al., ; Herrmann et al., ; Montgomery et al., ) and drug‐resistant isolates (Choi et al., ; Galarza et al., ), but the application of this technology to plant pathogen detection and characterization is still emerging. HRM analysis has been mainly used for differentiating Alternaria and Aspergillus species (Garganese et al., ; Xanthopoulou et al., ), and for genotyping Botrytis cinerea , Colletotrichum spp. and Venturia inaequalis or AvrLm4‐7 gene of Leptosphaeria maculans (Carpezat et al., ; Chatzidimopoulos et al., , ; Forcelini et al., ). To determine whether HRM could actually capture the SNP variants of a single gene with a unique melting curve, we first proceeded with a proof of concept by synthesizing and cloning wild‐type Avr6 along with multiple SNP variants, including a transversion (T to G), a single base deletion (G) and a five‐base deletion (GCGAT). The results clearly illustrate the defining power of HRM and support previous arguments that even a single base change could be distinguished using the technique (Druml & Cichna‐Markl, ; Twist et al., ). In 2018, Arsenault‐Labrecque et al. provided a detailed haplotype map for seven Avr genes ( 1a , 1b , 1c , 1d , 1k , 3a and 6 ) of P. sojae and were able to assign specific haplotypes to a distinct pathotype (Arsenault‐Labrecque et al., ). These data provided an invaluable source of sequences to design HRM primers around SNP sites and to use HRM assays to assign pathotypes to 12 P. sojae isolates with a different range of haplotypes. Our results showed that HRM was able to discriminate not only virulence/avirulence pathotype, but also exhibit unique curves for all tested haplotypes. For instance, isolate UL_082 exhibited a minor shift in the curve when tested for Avr1d . Further analyses of multiple alignments of the Avr1d amplification site revealed that isolate UL_082 had additional SNPs and HRM was able to precisely capture those variants (Figure ). To assess if HRM could accurately predict the haplotypes of unknown isolates, the same set of primers was used to test 12 P. sojae isolates collected across Quebec, Ontario and Manitoba. In all cases, the primer set consistently amplified all haplotypes of the six genes tested and demonstrated a consistent difference in the melting temperature of the corresponding amplified products from isolates containing different haplotypes. Throughout the different runs, the control melting curves were consistent and maintained similar melting peaks. Interestingly, the virulence profile as ascertained by the haplotype was perfectly corroborated by the phenotyping results obtained using the hydroponic assay. The indel markers proved to be functional markers in and around Avr genes, the amplification was stable, HRM curves were unique, the genotype was clear and the pathotype could be efficiently predicted. The HRM technique thus provides a rapid detection platform for pathotype and haplotype detection in P. sojae isolates and eliminates the cumbersome steps of phenotyping. One limitation of the HRM assay is its inability to effectively differentiate the SNP mutations caused by T/A substitution. Fortunately, we did not encounter this situation between two haplotypes of different virulence. If concerns arise regarding potential T/A substitutions in the HRM analysis, amplicons can be sequenced to determine the genetic variation and a probe‐based method targeting the variation can be incorporated in future assays. Cross‐validation with other methods increases confidence in HRM assay. Effectors are proteins secreted by many plant pathogens into the host plant cells to manipulate the host immune system and facilitate infection. These effectors can be highly variable among pathogen strains and are responsible for the differences in host compatibility observed among different pathogen populations, particularly in the case of P. sojae isolates (Rasoolizadeh et al., ; Toruño et al., ). HRM analysis can be used to detect sequence variations in and around genes encoding these effectors, which can provide valuable information on the genetic diversity of the pathogen population, help to understand the evolution of the pathogen, track the spread of specific strains, monitor the efficacy of disease control measures and design effective strategies for disease control. This HRM assay represents a novel approach to effectively detect genetic variations associated with virulence pathotypes of P. sojae . The results from this study were all based on pure P. sojae isolates that had been obtained from soil samples. To improve the diagnostic procedure even further, additional experiments could be conducted. For instance, future efforts could be devoted to expanding these assays to detect P. sojae pathotypes directly from plant or baiting samples or even from gDNA isolated directly from soil. Moreover, attempts to multiplex the HRM assay would reduce time and cost, if precision is not altered. In conclusion, we have developed a new diagnostic tool based on HRM analysis to differentiate multiple haplotypes associated with six different Avr genes ( 1b , 1c , 1d , 1k , 3a and 6 ) genes from P. sojae . The HRM analysis of the amplicons successfully identified the haplotypes of those genes in all 24 P. sojae isolates through distinct curve profiles, allowing us to discriminate pathotypes at the molecular level through the HRM curves. HRM can thus serve as a powerful diagnostic tool to identify and distinguish P. sojae isolates at the haplotype level.   EXPERIMENTAL PROCEDURES 4.1 Cloning of Avr6 variants To develop the initial proof of concept, we designed and synthesized four different variants of Avr6 CDS as gBlocks (IDT Inc.). These variants comprised (1) a wild‐type Avr6 (wt) from reference genome, (2) a transversion mutation of T to G at the 218th nucleotide from the start codon (T218G), (3) a deletion of G at the 214th nucleotide from the start codon (G214X) and (4) deletion of five nucleotides 214–218 from the start codon (214‐5X) (Figure ). The wild type and variants were synthesized as gBlocks, poly(A)‐tailed using Taq DNA polymerase (NEB) and cloned into pGEM‐T Easy vector (Promega) following the manufacturer's instructions. Cloned vectors were transformed into competent Escherichia coli (ThermoFisher) cells. Cloning was verified by PCR and positive colonies were propagated overnight in Luria Bertani liquid medium. Plasmids were isolated (QIAprep Spin Miniprep Kit; Qiagen) and used as templates for HRM analysis. 4.2 P. sojae isolates, inoculum preparation and hydroponic assay All P. sojae isolates used in this study (Table ) were sampled across Quebec, Ontario and Manitoba from commercial and experimental soybean fields (Tremblay et al., ). Individual P. sojae isolates were baited from soil samples using the soybean variety Harosoy or Williams following the procedures outlined in Tremblay et al. . The single‐spore isolates were maintained on clarified V8 agar (20%) and for long‐term storage agar pieces were stored in water at room temperature or 4°C. The inoculum for hydroponic assays was prepared by blending 12‐day‐old cultures grown on clarified V8 Phytagel medium (V8 20%, Phytagel 4 g/L) with 60 mL of sterile water in a commercial blender. The oospore concentration was determined from the slurry and adjusted to 10 6 oospores/mL (Lebreton et al., ; Tremblay et al., ). To validate the results obtained from HRM assays, 16 P. sojae isolates (four characterized by HRM and used as reference, and 12 uncharacterized) were subjected to hydroponic bioassays developed by Lebreton et al. . Soybean differentials possessing different Rps genes (Haro13 [ Rps1b ], Haro14 [ Rps1c ], Haro16 [ Rps1d ], Haro15 [ Rps1k ], Haro3272 [ Rps3a , 7 ] and Haro6272 [ Rps6 , 7 ]) were inoculated with P. sojae isolates as described in Tremblay et al. . Briefly, soybean seeds were sown in vermiculite and 5 days after seeding, plantlets were transferred into the hydroponic system containing the nutrient solution. The hydroponic system was inoculated with 10 6 oospores at 24 h after transfer of seedlings. At 14 days post‐inoculation (dpi), plants were scored as resistant or susceptible to the isolate tested. Each isolate was characterized in two independent experiments with two biological replications. Soybean seedlings were scored on a 1 to 5 scale as described by Lebreton et al. , where 1 = none to limited root symptoms and 5 = mortality and advanced root necrosis. Dunnett's test was used to determine the pathotype of P. sojae isolates. 4.3 Genomic DNA isolation P. sojae isolates were grown on cellophane paper placed on clarified V8 agar (20%) for 7 days at 28°C. Mycelial mats were harvested and transferred to tubes containing two beads. The samples were homogenized (4 m/s × 2 cycles of 30 s with a 40 s pause) with an Omni Bead Ruptor 24 (OMNI International) and genomic DNA was extracted using a CTAB method (Werth et al., ). DNA was eluted with 100 μL of TE buffer, quantified using a Qubit dsDNA BR assay kit (Invitrogen), normalized to 2 ng/μL and 2.5 μL was used for HRM analysis. The HRM assay was performed using DNA at concentrations ranging from 5 to 50 ng per reaction, without any change in uniformity or effectiveness. 4.4 PCR and HRM analysis of P. sojae Avr genes For successful HRM analysis, the target amplicon should be small, and the HRM primer binding sites should flank the variable regions. Shorter PCR amplicons are likely to produce distinguishable melt curve than longer amplicons with similar variants. Hence, our HRM primers were designed to amplify fragments of 120 to 160 bp. A total of 31 P. sojae isolates were collected across Ontario and Québec and sequenced using Illumina HiSeq 2500 (Arsenault‐Labrecque et al., ). For all tested Avr genes ( Avr1b , 1c , 1d , 1k , 3a and 6 ) multiple alignments were carried out using the coding sequence and 2 kb upstream region (Figures , ) using CLC‐Genomics workbench (Qiagen). Primers were designed manually around the polymorphic sites with melting temperature around 60°C (Table ). To ensure primer specificity, all primers were subjected to a BLAST search against the Oomycetes nr sequence database using NCBI primer‐BLAST. Primers that exhibited high specificity to the target region and had five or more mismatches in the off‐target sites were included in this study. For genotyping Avr1a three discriminative primers pairs are required for pathotyping and these primers are designed far from the Avr1a coding sequence (Dussault‐Benoit et al., ). As the goal of this study is to discriminate pathotypes using single primer pairs, Avr1a was excluded from this study. The HRM curve analysis was performed on a magnetic induction cycler (MIC) qPCR instrument (Bio Molecular Systems) using Precision Melt Supermix (BioRad) in a 20 μL reaction with 1× Precision Melt Supermix, each primer at a concentration of 300 nM and 5 ng genomic DNA in a MIC‐tubes (Bio Molecular Systems). Conditions for PCR were as follows: an initial denaturation step at 95°C for 3 min, followed by 40 cycles of 95°C for 10 s, 59°C for 30 s, 72°C for 30 s and final extension step at 72°C for 5 min with fluorescence reading at the end of each extension step. The qPCR was followed by a melting programme where the amplicon was heated from 70 to 98°C by ramping up the temperature at 0.2°C/s with a continuous signal acquisition. The HRM curve data were analysed, normalized and then converted to difference plots using the in‐built HRM analysis software (Bio Molecular Systems). Experiments were repeated twice with three technical replicates.   Cloning of Avr6 variants To develop the initial proof of concept, we designed and synthesized four different variants of Avr6 CDS as gBlocks (IDT Inc.). These variants comprised (1) a wild‐type Avr6 (wt) from reference genome, (2) a transversion mutation of T to G at the 218th nucleotide from the start codon (T218G), (3) a deletion of G at the 214th nucleotide from the start codon (G214X) and (4) deletion of five nucleotides 214–218 from the start codon (214‐5X) (Figure ). The wild type and variants were synthesized as gBlocks, poly(A)‐tailed using Taq DNA polymerase (NEB) and cloned into pGEM‐T Easy vector (Promega) following the manufacturer's instructions. Cloned vectors were transformed into competent Escherichia coli (ThermoFisher) cells. Cloning was verified by PCR and positive colonies were propagated overnight in Luria Bertani liquid medium. Plasmids were isolated (QIAprep Spin Miniprep Kit; Qiagen) and used as templates for HRM analysis.   P. sojae isolates, inoculum preparation and hydroponic assay All P. sojae isolates used in this study (Table ) were sampled across Quebec, Ontario and Manitoba from commercial and experimental soybean fields (Tremblay et al., ). Individual P. sojae isolates were baited from soil samples using the soybean variety Harosoy or Williams following the procedures outlined in Tremblay et al. . The single‐spore isolates were maintained on clarified V8 agar (20%) and for long‐term storage agar pieces were stored in water at room temperature or 4°C. The inoculum for hydroponic assays was prepared by blending 12‐day‐old cultures grown on clarified V8 Phytagel medium (V8 20%, Phytagel 4 g/L) with 60 mL of sterile water in a commercial blender. The oospore concentration was determined from the slurry and adjusted to 10 6 oospores/mL (Lebreton et al., ; Tremblay et al., ). To validate the results obtained from HRM assays, 16 P. sojae isolates (four characterized by HRM and used as reference, and 12 uncharacterized) were subjected to hydroponic bioassays developed by Lebreton et al. . Soybean differentials possessing different Rps genes (Haro13 [ Rps1b ], Haro14 [ Rps1c ], Haro16 [ Rps1d ], Haro15 [ Rps1k ], Haro3272 [ Rps3a , 7 ] and Haro6272 [ Rps6 , 7 ]) were inoculated with P. sojae isolates as described in Tremblay et al. . Briefly, soybean seeds were sown in vermiculite and 5 days after seeding, plantlets were transferred into the hydroponic system containing the nutrient solution. The hydroponic system was inoculated with 10 6 oospores at 24 h after transfer of seedlings. At 14 days post‐inoculation (dpi), plants were scored as resistant or susceptible to the isolate tested. Each isolate was characterized in two independent experiments with two biological replications. Soybean seedlings were scored on a 1 to 5 scale as described by Lebreton et al. , where 1 = none to limited root symptoms and 5 = mortality and advanced root necrosis. Dunnett's test was used to determine the pathotype of P. sojae isolates.   Genomic DNA isolation P. sojae isolates were grown on cellophane paper placed on clarified V8 agar (20%) for 7 days at 28°C. Mycelial mats were harvested and transferred to tubes containing two beads. The samples were homogenized (4 m/s × 2 cycles of 30 s with a 40 s pause) with an Omni Bead Ruptor 24 (OMNI International) and genomic DNA was extracted using a CTAB method (Werth et al., ). DNA was eluted with 100 μL of TE buffer, quantified using a Qubit dsDNA BR assay kit (Invitrogen), normalized to 2 ng/μL and 2.5 μL was used for HRM analysis. The HRM assay was performed using DNA at concentrations ranging from 5 to 50 ng per reaction, without any change in uniformity or effectiveness.   PCR and HRM analysis of P. sojae Avr genes For successful HRM analysis, the target amplicon should be small, and the HRM primer binding sites should flank the variable regions. Shorter PCR amplicons are likely to produce distinguishable melt curve than longer amplicons with similar variants. Hence, our HRM primers were designed to amplify fragments of 120 to 160 bp. A total of 31 P. sojae isolates were collected across Ontario and Québec and sequenced using Illumina HiSeq 2500 (Arsenault‐Labrecque et al., ). For all tested Avr genes ( Avr1b , 1c , 1d , 1k , 3a and 6 ) multiple alignments were carried out using the coding sequence and 2 kb upstream region (Figures , ) using CLC‐Genomics workbench (Qiagen). Primers were designed manually around the polymorphic sites with melting temperature around 60°C (Table ). To ensure primer specificity, all primers were subjected to a BLAST search against the Oomycetes nr sequence database using NCBI primer‐BLAST. Primers that exhibited high specificity to the target region and had five or more mismatches in the off‐target sites were included in this study. For genotyping Avr1a three discriminative primers pairs are required for pathotyping and these primers are designed far from the Avr1a coding sequence (Dussault‐Benoit et al., ). As the goal of this study is to discriminate pathotypes using single primer pairs, Avr1a was excluded from this study. The HRM curve analysis was performed on a magnetic induction cycler (MIC) qPCR instrument (Bio Molecular Systems) using Precision Melt Supermix (BioRad) in a 20 μL reaction with 1× Precision Melt Supermix, each primer at a concentration of 300 nM and 5 ng genomic DNA in a MIC‐tubes (Bio Molecular Systems). Conditions for PCR were as follows: an initial denaturation step at 95°C for 3 min, followed by 40 cycles of 95°C for 10 s, 59°C for 30 s, 72°C for 30 s and final extension step at 72°C for 5 min with fluorescence reading at the end of each extension step. The qPCR was followed by a melting programme where the amplicon was heated from 70 to 98°C by ramping up the temperature at 0.2°C/s with a continuous signal acquisition. The HRM curve data were analysed, normalized and then converted to difference plots using the in‐built HRM analysis software (Bio Molecular Systems). Experiments were repeated twice with three technical replicates.   The authors declare no conflict of interest.   Figure S1. For proof of concept, Avr6 wild type, Avr6 with a single nucleotide substitution (T218G), Avr6 with single nucleotide deletion (G214X) and Avr6 with five nucleotide deletions (214‐218X) was synthesized as gBlock, cloned in pGEM‐T Easy vector and used as template for PCR and high‐resolution melt curve analysis was performed. Primer binding sites are marked with solid arrows, size of amplicon is 120 bp. Click here for additional data file. Figure S2. (a) Multiple alignment of Avr1b HRM primer binding sites among 31 Phytophthora sojae isolates. Arrows (black) indicate primer binding sites, deletions are marked as hyphens (−). (b) Variants identified within the target region. Click here for additional data file. Figure S3. (a) Multiple alignment of Avr1c HRM primer binding sites among 31 Phytophthora sojae isolates. Arrows (black) indicate primer binding sites, deletions are marked as hyphens (−). (b) Variants identified within the target region. Click here for additional data file. Figure S4. (a) Multiple alignment of Avr1d HRM primer binding sites among 31 Phytophthora sojae isolates. Arrows (black) indicate primer binding sites, deletions are marked as hyphens (−). (b) Variants identified within the target region. Click here for additional data file. Figure S5. (a) Multiple alignment of Avr1k HRM primer binding sites among 31 Phytophthora sojae isolates. Arrows (black) indicate primer binding sites, deletions are marked as hyphens (−). (b) Variants identified within the target region. Click here for additional data file. Figure S6. (a) Multiple alignment of Avr3a HRM primer binding sites among 31 Phytophthora sojae isolates. Arrows (black) indicate primer binding sites, deletions are marked as hyphens (−). (b) Variants identified within the target region. Click here for additional data file. Figure S7. (a) Multiple alignment of Avr6 HRM primer binding sites among 31 Phytophthora sojae isolates. Arrows (black) indicate primer binding sites; deletions are marked as hyphens (−). (b) Variants identified within the target region. Click here for additional data file. Figure S8. Phenotyping of Phytophthora sojae isolates. To validate HRM‐based pathotype prediction, roots were inoculated with reference isolates (UL_192, UL_253) and 12 field isolates (UL_796, UL_800, UL_817, UL_818, UL_820, UL_826, UL_829, UL_842, UL_848, UL_851, UL_860, UL_865) on soybean differentials containing corresponding Rps genes ( Rps1b , Rps1c , Rps1d , Rps1k , Rps3a and Rps6 ) in hydroponics. Two weeks post‐inoculation, disease progression was observed and reaction scored as avirulent (Avr) or virulent (Vir) according to Lebreton et al. . Williams and Harosoy were used as Rps controls. Two plants were tested in each experiment, repeated twice with similar results. Click here for additional data file. Table S1. List of 12 Phytophthora sojae isolates previously phenotypically and genotypical characterized Click here for additional data file. Table S2. List of Phytophthora sojae isolates tested in this study Click here for additional data file. Table S3. List of primers used in this study Click here for additional data file.   