Identification and molecular mapping of a major gene conferring resistance to Phytophthora sansomeana in soybean 'Colfax'.

KEY MESSAGE: The first single dominant resistance gene contributing major resistance to the oomycete pathogen Phytophthora sansomeana was identified and mapped from soybean 'Colfax'. Phytophthora root rot (PRR) is one of the most important diseases in soybean (Glycine max). PRR is well known to be caused by Phytophthora sojae, but recent studies showed that P. sansomeana also causes extensive root rot of soybean. Depending upon the isolate, it might produce aggressive symptoms, especially in seeds and seedlings. Unlike P. sojae which can be effectively managed by Rps genes, no known major resistance genes have yet been reported for P. sansomeana. Our previous study screened 470 soybean germplasm lines for resistance to P. sansomeana and found that soybean 'Colfax' (PI 573008) carries major resistance to the pathogen. In this study, we crossed 'Colfax' with a susceptible parent, 'Senaki', and developed three mapping populations with a total of 234 F2:3 families. Inheritance pattern analysis indicated a 1:2:1 ratio for resistant: segregating: susceptible lines among all the three populations, indicating a single dominant gene conferring the resistance in 'Colfax' (designated as Rpsan1). Linkage analysis using extreme phenotypes anchored Rpsan1 to a 30 Mb region on chromosome 3. By selecting nine polymorphic SNP markers within the region, Rpsan1 was genetically delimited into a 21.3 cM region between Gm03_4487138_A_C and Gm03_5451606_A_C, which corresponds to a 1.06 Mb genomic region containing nine NBS-LRR genes based on Gmax2.0 assembly. The mapping results were then validated using two breeding populations derived from 'E12076T-03' × 'Colfax' and 'E16099' × 'Colfax'. Marker-assisted resistance spectrum analyses with 9 additional isolates of P. sansomeana indicated that Rpsan1 may be effective towards a broader range of P. sansomeana isolates and has strong merit in protecting soybean to this pathogen in the future.

Multistate Sensitivity Monitoring of Fusarium virguliforme to the SDHI Fungicides Fluopyram and Pydiflumetofen in the United States.

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is an important yield-limiting disease of soybean (Glycine max). From 1996 to 2022, cumulative yield losses attributed to SDS in North America totaled over 25 million metric tons, which was valued at over US $7.8 billion. Seed treatments are widely used to manage SDS by reducing early season soybean root infection by F. virguliforme. Fluopyram (succinate dehydrogenase inhibitor [SDHI] - FRAC 7), a fungicide seed treatment for SDS management, has been registered for use on soybean in the United States since 2014. A baseline sensitivity study conducted in 2014 evaluated 130 F. virguliforme isolates collected from five states to fluopyram in a mycelial growth inhibition assay and reported a mean EC50 of 3.35 mg/liter. This baseline study provided the foundation for the objectives of this research: to detect any statistically significant change in fluopyram sensitivity over time and geographical regions within the United States and to investigate sensitivity to the fungicide pydiflumetofen. We repeated fluopyram sensitivity testing on a panel of 80 historical F. virguliforme isolates collected from 2006 to 2013 (76 of which were used in the baseline study) and conducted testing on 123 contemporary isolates collected from 2016 to 2022 from 11 states. This study estimated a mean absolute EC50 of 3.95 mg/liter in isolates collected from 2006 to 2013 and a mean absolute EC50 of 4.19 mg/liter in those collected in 2016 to 2022. There was no significant change in fluopyram sensitivity (P = 0.1) identified between the historical and contemporary isolates. A subset of 23 isolates, tested against pydiflumetofen under the same conditions, estimated an absolute mean EC50 of 0.11 mg/liter. Moderate correlation was detected between fluopyram and pydiflumetofen sensitivity estimates (R = 0.53; P < 0.001). These findings enable future fluopyram and pydiflumetofen resistance monitoring and inform current soybean SDS management strategies in a regional and national context.

A global-temporal analysis on Phytophthora sojae resistance-gene efficacy.

Plant disease resistance genes are widely used in agriculture to reduce disease outbreaks and epidemics and ensure global food security. In soybean, Rps (Resistance to Phytophthora sojae) genes are used to manage Phytophthora sojae, a major oomycete pathogen that causes Phytophthora stem and root rot (PRR) worldwide. This study aims to identify temporal changes in P. sojae pathotype complexity, diversity, and Rps gene efficacy. Pathotype data was collected from 5121 isolates of P. sojae, derived from 29 surveys conducted between 1990 and 2019 across the United States, Argentina, Canada, and China. This systematic review shows a loss of efficacy of specific Rps genes utilized for disease management and a significant increase in the pathotype diversity of isolates over time. This study finds that the most widely deployed Rps genes used to manage PRR globally, Rps1a, Rps1c and Rps1k, are no longer effective for PRR management in the United States, Argentina, and Canada. This systematic review emphasizes the need to widely introduce new sources of resistance to P. sojae, such as Rps3a, Rps6, or Rps11, into commercial cultivars to effectively manage PRR going forward.

Identification and characterization of pleiotropic and epistatic QDRL conferring partial resistance to Pythium irregulare and P. sylvaticum in soybean.

KEY MESSAGE: Pleiotropic and epistatic quantitative disease resistance loci (QDRL) were identified for soybean partial resistance to different isolates of Pythium irregulare and Pythium sylvaticum. Pythium root rot is an important seedling disease of soybean [Glycine max (L.) Merr.], a crop grown worldwide for protein and oil content. Pythium irregulare and P. sylvaticum are two of the most prevalent and aggressive Pythium species in soybean producing regions in the North Central U.S. Few studies have been conducted to identify soybean resistance for management against these two pathogens. In this study, a mapping population (derived from E13390 x E13901) with 228 F4:5 recombinant inbred lines were screened against P. irregulare isolate MISO 11-6 and P. sylvaticum isolate C-MISO2-2-30 for QDRL mapping. Correlation analysis indicated significant positive correlations between soybean responses to the two pathogens, and a pleiotropic QDRL (qPirr16.1) was identified. Further investigation found that the qPirr16.1 imparts dominant resistance against P. irregulare, but recessive resistance against P. sylvaticum. In addition, two QDRL, qPsyl15.1, and qPsyl18.1 were identified for partial resistance to P. sylvaticum. Further analysis revealed epistatic interactions between qPirr16.1 and qPsyl15.1 for RRW and DRX, whereas qPsyl18.1 contributed resistance to RSE. Marker-assisted resistance spectrum analysis using F6:7 progeny lines verified the resistance of qPirr16.1 against four additional P. irregulare isolates. Intriguingly, although the epistatic interaction of qPirr16.1 and qPsyl15.1 can be confirmed using two additional isolates of P. sylvaticum, the interaction appears to be suppressed for the other two P. sylvaticum isolates. An 'epistatic gene-for-gene' model was proposed to explain the isolate-specific epistatic interactions. The integration of the QDRL into elite soybean lines containing all the desirable alleles has been initiated.

Phytophthora sojae Pathotype Distribution and Fungicide Sensitivity in Michigan.

Identifying the pathotype structure of a Phytophthora sojae population is crucial for the effective management of Phytophthora stem and root rot of soybean (PRR). P. sojae has been successfully managed with major resistance genes, partial resistance, and fungicide seed treatments. However, prolonged use of resistance genes or fungicides can cause pathogen populations to adapt over time, rendering resistance genes or fungicides ineffective. A statewide survey was conducted to characterize this pathotype structure and fungicide sensitivity of P. sojae within Michigan. Soil samples were collected from 69 fields with a history of PRR and fields having consistent plant stand establishment issues. Eighty-three isolates of P. sojae were obtained, and hypocotyl inoculations were performed on 14 differential soybean cultivars, all of which carry a single Rps gene or no resistance gene. The survey identified a loss of effectiveness of Rps genes 1b, 1k, 3b, and 6, compared with a previous survey conducted in Michigan from 1993 to 1997. Three effective resistance genes were identified for P. sojae management in Michigan; Rps 3a, 3c, and 4. Additionally, the effective concentration of common seed treatment fungicides to inhibit mycelial growth by 50% (EC50) was determined. No P. sojae isolates were insensitive to the tested chemistries with mean EC50 values of 2.60 × 10-2 µg/ml for ethaboxam, 3.03 × 10-2 µg/ml for mefenoxam, 2.88 × 10-4 µg/ml for oxathiapiprolin, and 5.08 × 10-2 µg/ml for pyraclostrobin. Results suggest that while there has been a significant shift in Rps gene effectiveness, seed treatments are still effective for early season management of this disease.

Molecular mapping of quantitative disease resistance loci for soybean partial resistance to Phytophthora sansomeana.

KEY MESSAGE: Two soybean QDRL were identified with additive interaction to P. sansomeana isolate MPS17-22. Further analyses uncovered four interaction patterns between the two QDRL and seven additional P. sansomeana isolates. Phytophthora sansomeana is a recently recognized species that contributes to root rot in soybean. Previous studies indicated that P. sansomeana is widely distributed among soybean growing regions and has a much wider host range than P. sojae, a well-known pathogen of soybean. Unlike P. sojae, no known disease resistance genes have been documented that can effectively control P. sansomeana. Therefore, it is important to identify resistance that can be quickly integrated into future soybean varieties. E13901 is an improved soybean line that confers partial resistance to P. sansomeana. A mapping population of 228 F4:5 families was developed from a cross between E13901 and a susceptible improved soybean variety E13390. Using a composite interval mapping method, two quantitative disease resistance loci (QDRL) were identified on Chromosomes 5 (designated qPsan5.1) and 16 (designated qPsan16.1), respectively. qPsan5.1 was mapped at 54.71 cM between Gm05_32565157_T_C and Gm05_32327497_T_C. qPsan5.1 was contributed by E13390 and explained about 6% of the disease resistance variation. qPsan16.1 was located at 39.01 cM between Gm16_35700223_G_T and Gm16_35933600/ Gm16_35816475. qPsan16.1 was from E13901 and could explain 5.5% of partial disease resistance. Further analysis indicated an additive interaction of qPsan5.1 and qPsan16.1 against P. sansomeana isolate MPS17-22. Marker assisted resistance spectrum analysis and progeny tests verified the two QDRL and their interaction patterns with other P. sansomeana isolates. Both QDRL can be quickly integrated into soybean varieties using marker assisted selection.

Validation of a Preformulated, Field Deployable, Recombinase Polymerase Amplification Assay for Phytophthora Species.

Recombinase polymerase amplification (RPA) assays are valuable molecular diagnostic tools that can detect and identify plant pathogens in the field without time-consuming DNA extractions. Historically, RPA assay reagents were commercially available as a lyophilized pellet in microfuge strip tubes, but have become available in liquid form more recently-both require the addition of primers and probes prior to use, which can be challenging to handle in a field setting. Lyophilization of primers and probes, along with RPA reagents, contained within a single tube limits the risk of contamination, eliminates the need for refrigeration, as the lyophilized reagents are stable at ambient temperatures, and simplifies field use of the assays. This study investigates the potential effect of preformulation on assay performance using a previously validated Phytophthora genus-specific RPA assay, lyophilized with primers and probes included with the RPA reagents. The preformulated lyophilized Phytophthora RPA assay was compared with a quantitative polymerase chain reaction (qPCR) assay and commercially available RPA kits using three qPCR platforms (BioRad CFX96, QuantStudio 6 and Applied Biosystems ViiA7) and one isothermal platform (Axxin T16-ISO RPA), with experiments run in four separate labs. The assay was tested for sensitivity (ranging from 500 to 0.33 pg of DNA) and specificity using purified oomycete DNA, as well as crude extracts of Phytophthora-infected and non-infected plants. The limit of detection (LOD) using purified DNA was 33 pg in the CFX96 and ViiA7 qPCR platforms using the preformulated kits, while the Axxin T16-ISO RPA chamber and the QuantStudio 6 platform could detect down to 3.3 pg with or without added plant extract. The LOD using a crude plant extract for the BioRad CFX96 was 330 pg, whereas the LOD for the ViiA7 system was 33 pg. These trials demonstrate the consistency and uniformity of pathogen detection with preformulated RPA kits for Phytophthora detection when conducted by different labs using different instruments for measuring results.

hagis, an R Package Resource for Pathotype Analysis of Phytophthora sojae Populations Causing Stem and Root Rot of Soybean.

Phytophthora sojae is a significant pathogen of soybean worldwide. Pathotype surveys for Phytophthora sojae are conducted to monitor resistance gene efficacy and determine if new resistance genes are needed. Valuable measurements for pathotype analysis include the distribution of susceptible reactions, pathotype complexity, pathotype frequency, and diversity indices for pathotype distributions. Previously the Habgood-Gilmour Spreadsheet (HaGiS), written in Microsoft Excel, was used for data analysis. However, the growing popularity of the R programming language in plant pathology and desire for reproducible research made HaGiS a prime candidate for conversion into an R package. Here we report on the development and use of an R package, hagis, that can be used to produce all outputs from the HaGiS Excel sheet for P. sojae or other gene-for-gene pathosystem studies.