NanoViromics: long-read sequencing of dsRNA for plant virus and viroid rapid detection.

There is a global need for identifying viral pathogens, as well as for providing certified clean plant materials, in order to limit the spread of viral diseases. A key component of management programs for viral-like diseases is having a diagnostic tool that is quick, reliable, inexpensive, and easy to use. We have developed and validated a dsRNA-based nanopore sequencing protocol as a reliable method for detecting viruses and viroids in grapevines. We compared our method, which we term direct-cDNA sequencing from dsRNA (dsRNAcD), to direct RNA sequencing from rRNA-depleted total RNA (rdTotalRNA), and found that it provided more viral reads from infected samples. Indeed, dsRNAcD was able to detect all of the viruses and viroids detected using Illumina MiSeq sequencing (dsRNA-MiSeq). Furthermore, dsRNAcD sequencing was also able to detect low-abundance viruses that rdTotalRNA sequencing failed to detect. Additionally, rdTotalRNA sequencing resulted in a false-positive viroid identification due to the misannotation of a host-driven read. Two taxonomic classification workflows, DIAMOND & MEGAN (DIA & MEG) and Centrifuge & Recentrifuge (Cent & Rec), were also evaluated for quick and accurate read classification. Although the results from both workflows were similar, we identified pros and cons for both workflows. Our study shows that dsRNAcD sequencing and the proposed data analysis workflows are suitable for consistent detection of viruses and viroids, particularly in grapevines where mixed viral infections are common.

Phylogenetic and Evolutionary Studies of Grapevine Pinot Gris Virus Isolates from Canada.

This study investigated the phylogenetic relationship of grapevine Pinot gris virus (GPGV) isolates from Canada with GPGV isolates reported worldwide. Full-length genomes of 25 GPGV isolates representing the main four grape-growing regions in Canada (British Columbia, Ontario, Nova Scotia and Quebec) were sequenced and compared to genomes of 43 GPGV isolates representing eight countries and three continents. Phylogenetic analysis based on full genome sequences revealed an unambiguous separation of North American GPGV isolates with isolates from Europe and Asia. Within the North American clade, GPGV isolates from the USA segregated into a distinct subclade, whereas the relationships amongst GPGV isolates from different regions of Canada were not clearly defined. The phylogenetic analysis of the overlapping regions of MP and CP genes involving 169 isolates from 14 countries resulted in two distinctive clades, which were seemingly independent of their country of origin. Clade 1 included the majority of asymptomatic isolates (81% asymptomatic), whereas clade 2 was predominantly formed of symptomatic isolates (78% symptomatic). This research is the first study focused on the genetic variability and origin of GPGV in Canada.

Competition Between Plasmopara viticola Clade riparia and Clade aestivalis: A Race to Lead Grape Downy Mildew Epidemics.

There is evidence of five clades of Plasmopara viticola in the world. Only two clades, riparia and aestivalis, have been identified as responsible for downy mildew epidemics in Quebec, Canada. It was reported in 2021 that epidemics caused by clade riparia start 2 or 3 weeks before those caused by clade aestivalis and that clade aestivalis was more aggressive than clade riparia. The objective of this work was to study the competition between P. viticola clade riparia (A) and clade aestivalis (B) and to compare the aggressiveness of both clades in mono- and coinfection situations. Suspensions of sporangia from both clades with six percentage combinations (AB 100-0; AB 89-11; AB 74-26; AB 46-54; AB 23-77; and AB 0-100) were inoculated on leaf discs (cultivar Vidal), and three other combinations (AB 88-12; AB 68-32; and AB 47-53) were inoculated on living leaves of grape plants (cultivar Vidal). Then, sporangium production, expressed as the percentage of sporangia produced by each clade, was estimated on leaf discs after eight cycles of infection-sporulation and then validated on living grape leaves after five cycles. The aggressiveness of clades in monoinfection situations on leaf discs was compared with that in coinfection situations. The results show that the percentage of sporangia produced by clade aestivalis increases with the infection-sporulation cycle while that produced by clade riparia decreases. The area under the sporangium production progress curve (AUSPPC) of clade aestivalis was significantly higher than that of clade riparia. The aggressiveness of P. viticola clades riparia and aestivalis in coinfection situations was different from that in monoinfection situations and was strongly influenced by the percentage of each clade in competition. These results suggest that, on the grapevine cultivar Vidal, P. viticola clade aestivalis is more competitive than clade riparia and that the percentage of each clade present in the vineyard should be considered for management of downy mildew.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

A Diverse Virome of Leafroll-Infected Grapevine Unveiled by dsRNA Sequencing.

Quebec is the third-largest wine grape producing province in Canada, and the industry is constantly expanding. Traditionally, 90% of the grapevine cultivars grown in Quebec were winter hardy and largely dominated by interspecific hybrid Vitis sp. cultivars. Over the years, the winter protection techniques adopted by growers and climate changes have offered an opportunity to establish V. vinifera L. cultivars (e.g., Pinot noir). We characterized the virome of leafroll-infected interspecific hybrid cultivar and compared it to the virome of V. vinifera cultivar to support and facilitate the transition of the industry. A dsRNA sequencing method was used to sequence symptomatic and asymptomatic grapevine leaves of different cultivars. The results suggested a complex virome in terms of composition, abundance, richness, and phylogenetic diversity. Three viruses, grapevine Rupestris stem pitting-associated virus, grapevine leafroll-associated virus (GLRaV) 3 and 2 and hop stunt viroid (HSVd) largely dominated the virome. However, their presence and abundance varied among grapevine cultivars. The symptomless grapevine cultivar Vidal was frequently infected by multiple virus and viroid species and different strains of the same virus, including GLRaV-3 and 2. Our data show that viruses and viroids associated with the highest number of grapevines expressing symptoms included HSVd, GLRaV-3 and GLRaV-2, in gradient order. However, co-occurrence analysis revealed that the presence of GLRaV species was randomly associated with the development of virus-like symptoms. These findings and their implications for grapevine leafroll disease management are discussed.

Meta-Analytic and Economic Approaches for Evaluation of Pesticide Impact on Sclerotinia Stem Rot Control and Soybean Yield in the North Central United States.

As complete host resistance in soybean has not been achieved, Sclerotinia stem rot (SSR) caused by Sclerotinia sclerotiorum continues to be of major economic concern for farmers. Thus, chemical control remains a prevalent disease management strategy. Pesticide evaluations were conducted in Illinois, Iowa, Michigan, Minnesota, New Jersey, and Wisconsin from 2009 to 2016, for a total of 25 site-years (n = 2,057 plot-level data points). These studies were used in network meta-analyses to evaluate the impact of 10 popular pesticide active ingredients, and seven common application timings on SSR control and yield benefit, compared with not treating with a pesticide. Boscalid and picoxystrobin frequently offered the best reductions in disease severity and best yield benefit (P < 0.0001). Pesticide applications (one- or two-spray programs) made during the bloom period provided significant reductions in disease severity index (DIX) (P < 0.0001) and led to significant yield benefits (P = 0.0009). Data from these studies were also used in nonlinear regression analyses to determine the effect of DIX on soybean yield. A three-parameter logistic model was found to best describe soybean yield loss (pseudo-R2 = 0.309). In modern soybean cultivars, yield loss due to SSR does not occur until 20 to 25% DIX, and considerable yield loss (-697 kg ha-1 or -10 bu acre-1) is observed at 68% DIX. Further analyses identified several pesticides and programs that resulted in greater than 60% probability for return on investment under high disease levels.

Validating Sclerotinia sclerotiorum Apothecial Models to Predict Sclerotinia Stem Rot in Soybean (Glycine max) Fields.

In soybean, Sclerotinia sclerotiorum apothecia are the sources of primary inoculum (ascospores) critical for Sclerotinia stem rot (SSR) development. We recently developed logistic regression models to predict the presence of apothecia in irrigated and nonirrigated soybean fields. In 2017, small-plot trials were established to validate two weather-based models (one for irrigated fields and one for nonirrigated fields) to predict SSR development. Additionally, apothecial scouting and disease monitoring were conducted in 60 commercial fields in three states between 2016 and 2017 to evaluate model accuracy across the growing region. Site-specific air temperature, relative humidity, and wind speed data were obtained through the Integrated Pest Information Platform for Extension and Education (iPiPE) and Dark Sky weather networks. Across all locations, iPiPE-driven model predictions during the soybean flowering period (R1 to R4 growth stages) explained end-of-season disease observations with an accuracy of 81.8% using a probability action threshold of 35%. Dark Sky data, incorporating bias corrections for weather variables, explained end-of-season disease observations with 87.9% accuracy (in 2017 commercial locations in Wisconsin) using a 40% probability threshold. Overall, these validations indicate that these two weather-based apothecial models, using either weather data source, provide disease risk predictions that both reduce unnecessary chemical application and accurately advise applications at critical times.

Spatiotemporal Distribution Pattern of Sclerotinia sclerotiorum Apothecia is Modulated by Canopy Closure and Soil Temperature in an Irrigated Soybean Field.

Identifying the optimal timing for fungicide application is crucial in order to maximize the control of Sclerotinia stem rot (SSR), which is caused by Sclerotinia sclerotiorum. In this study, the impact of canopy closure and soil temperature on apothecia production was investigated to optimize fungicide application timing. Replicated soybean plots with a row spacing of 0.36 and 0.38 or 0.76 m were established in 2015 and 2016 in an irrigated soybean field at Michigan State University's Montcalm Research Center. The number of apothecia and ascospores and the incidence of SSR were monitored two times per week for 10 to 12 weeks. In both row-spacing trials, apothecia were observed earlier in 2016 (before the R1 growth stage) than in 2015 (between R1 and R2). The maximum number of apothecia was 50 times higher with the 0.36-m row spacing than with the 0.76-m row spacing in 2015 but was 2.5 times higher with the 0.76-m row spacing than with the 0.38-m row spacing in 2016, though the overall numbers were much lower in 2016. The apothecia distribution pattern was synchronized with the canopy closure pattern and the soil temperature profile. The peak number of apothecia was observed when canopy closure reached at least 50% and when average soil temperature in the row was between 21.5 and 23.5°C. In 91% of the cases, the presence of apothecia was observed when the percentage of light blocked was 70%, and no apothecia germinated in the absence of light or under full light exposure. During the first 50 days after plant emergence, the rate of canopy closure was higher in 2016 than in 2015, and the first diseased plant was observed earlier in 2016 (R2) than in 2015 (R5). Canopy closure and the distance of the sampling point from the soybean row explained much of the variability in the number of apothecia. These results can partially explain the inconsistent efficacy of fungicide applications based on the soybean growth stage and will be helpful for informing disease models and fine-tuning fungicide application strategies.

Case Study of an Epidemiological Approach Dissecting Historical Soybean Sclerotinia Stem Rot Observations and Identifying Environmental Predictors of Epidemics and Yield Loss.

Sclerotinia sclerotiorum is a significant threat to soybean production worldwide. In this study, an epidemiological approach was used to examine 11 years of historical data from a soybean management performance trial in order to advance our understanding of Sclerotinia stem rot (SSR) development and to identify environmental predictors of SSR epidemics and associated yield losses. Recursive partitioning analysis suggested that average air temperature and total precipitation in July were the most significant variables associated with disease severity. High levels of SSR disease severity index were observed when the average temperature in July was below 19.5°C and total precipitation in July was moderate, between 20 and 108.5 mm. A biphasic sigmoidal curve accurately described the relationship between SSR disease severity index (DSI) and yield, with a DSI threshold of 22, below which minimal yield loss was observed. A 10% increase in the DSI, from 22.0 to 24.2, led to an 11% decrease in yield, from 3,308.14 to 2,951.29 kg/ha. Also, a yield threshold (3,353 kg/ha) that was higher than the annual U.S. average soybean yield (3,039.7 kg/ha) was suggested as an expected yield under low or no SSR pressure in the U.S. Midwest. These thresholds can allow soybean stakeholders to assess the value of disease control and establish an SSR baseline for cost-effective management to protect yields. Because S. sclerotiorum has more than 400 plant host species, and because having quantitative information concerning crop losses is crucial for decision making, this study shows the usefulness of historical data on SSR and, hence, can serve as a model in other SSR pathosystems (canola, dry bean, potato, pea, and so on).

Weather-Based Models for Assessing the Risk of Sclerotinia sclerotiorum Apothecial Presence in Soybean (Glycine max) Fields.

Sclerotinia stem rot (SSR) epidemics in soybean, caused by Sclerotinia sclerotiorum, are currently responsible for annual yield reductions in the United States of up to 1 million metric tons. In-season disease management is largely dependent on chemical control but its efficiency and cost-effectiveness depends on both the chemistry used and the risk of apothecia formation, germination, and further dispersal of ascospores during susceptible soybean growth stages. Hence, accurate prediction of the S. sclerotiorum apothecial risk during the soybean flowering period could enable farmers to improve in-season SSR management. From 2014 to 2016, apothecial presence or absence was monitored in three irrigated (n = 1,505 plot-level observations) and six nonirrigated (n = 2,361 plot-level observations) field trials located in Iowa (n = 156), Michigan (n = 1,400), and Wisconsin (n = 2,310), for a total of 3,866 plot-level observations. Hourly air temperature, relative humidity, dew point, wind speed, leaf wetness, and rainfall were also monitored continuously, throughout the season, at each location using high-resolution gridded weather data. Logistic regression models were developed for irrigated and nonirrigated conditions using apothecial presence as a binary response variable. Agronomic variables (row width) and weather-related variables (defined as 30-day moving averages, prior to apothecial presence) were tested for their predictive ability. In irrigated soybean fields, apothecial presence was best explained by row width (r = -0.41, P < 0.0001), 30-day moving averages of daily maximum air temperature (r = 0.27, P < 0.0001), and daily maximum relative humidity (r = 0.16, P < 0.05). In nonirrigated fields, apothecial presence was best explained by using moving averages of daily maximum air temperature (r = -0.30, P < 0.0001) and wind speed (r = -0.27, P < 0.0001). These models correctly predicted (overall accuracy of 67 to 70%) apothecial presence during the soybean flowering period for four independent datasets (n = 1,102 plot-level observations or 30 daily mean observations).