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Phytophthora sojae Kaufmann and Gerdemann, which causes Phytophthora root rot, is a widespread pathogen that limits soybean production worldwide. Development of Phytophthora resistant cultivars carrying Phytophthora resistance Rps genes is a cost-effective approach in controlling this disease. For this mapping study of a novel Rps gene, 290 recombinant inbred lines (RILs) (F7 families) were developed by crossing the P. sojae resistant cultivar PI399036 with the P. sojae susceptible AR2 line, and were phenotyped for responses to a mixture of three P. sojae isolates that overcome most of the known Rps genes. Of these 290 RILs, 130 were homozygous resistant, 12 heterzygous and segregating for Phytophthora resistance, and 148 were recessive homozygous and susceptible. From this population, 59 RILs homozygous for Phytophthora sojae resistance and 61 susceptible to a mixture of P. sojae isolates R17 and Val12-11 or P7074 that overcome resistance encoded by known Rps genes mapped to Chromosome 18 were selected for mapping novel Rps gene. A single gene accounted for the 1:1 segregation of resistance and susceptibility among the RILs. The gene encoding the Phytophthora resistance mapped to a 5.8 cM interval between the SSR markers BARCSOYSSR_18_1840 and Sat_064 located in the lower arm of Chromosome 18. The gene is mapped 2.2 cM proximal to the NBSRps4/6-like sequence that was reported to co-segregate with the Phytophthora resistance genes Rps4 and Rps6. The gene is mapped to a highly recombinogenic, gene-rich genomic region carrying several nucleotide binding site-leucine rich repeat (NBS-LRR)-like genes. We named this novel gene as Rps12, which is expected to be an invaluable resource in breeding soybeans for Phytophthora resistance.

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean ( Glycine max [L.] Merrill). Yield losses attributed to P . sojae are devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverse P . sojae pathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection by P . sojae . In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions with P . sojae and a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis ( Arabidopsis thaliana ) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response against P . sojae . Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance to P . sojae .

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. Rps genes are used to manage the major soybean pathogen Phytophthora sojae , which causes Phytophthora stem and root rot (PRR). Here, the authors show that widely used Rps genes are no longer effective for managing PRR in the United States, Canada and Argentina.

For soybean, novel single dominant Resistance to Phytophthora sojae ( Rps) genes are sought to manage Phytophthora root and stem rot. In this study, resistance to P. sojae was mapped individually in four recombinant inbred line (RIL) populations derived from crosses of the susceptible cultivar Williams with PI 407985, PI 408029, PI 408097, and PI424477 previously identified as putative novel sources of disease resistance. Each population was screened for resistance with five to seven isolates of P. sojae separately over multiple F 7 –F 10 generations. Additionally, three of the populations were screened with inoculum from the combination of three P. sojae isolates (PPR), which comprised virulence to 14 Rps genes. Over 2,300 single-nucleotide polymorphism markers were used to construct genetic maps in each population to identify chromosomal regions associated with resistance to P. sojae . Resistance segregated as one or two genes to the individual isolates and one gene toward PPR in each population and mapped to chromosomes 3, 13, or 18 in one or more of the four RIL populations. Resistance to five isolates mapped to the same chromosome 3 region are as follows: OH7 (PI 424477 and PI408029), OH12168, OH7/8, PPR (PI 407985), and 1.S.1.1 (PI408029). The resistance regions on chromosome 13 also overlapped for OH1, OH25, OH-MIA (PI424477), PPR (PI 424477, PI 407985, and PI 408097), PPR and OH0217 (PI 408097), and OH4 (PI 408029), but were distinct for each population suggesting multiple genes confer resistance. Two regions were identified on chromosome 18 but all appear to map to known loci; notably, resistance to the combined inoculum (PPR) did not map at this locus. However, there are putative new alleles in three of four populations, three on chromosome 3 and two on chromosome 13 based on mapping location but also known virulence in the isolate used. This characterization of all the Rps genes segregating in these populations to these isolates will be informative for breeding, but the combined inoculum was able to map a novel loci. Furthermore, within each of these P. sojae isolates, there was virulence to more than the described Rps genes, and the effectiveness of the novel genes requires testing in larger populations.

Phyllachora maydis is a fungal pathogen causing tar spot of corn ( Zea mays L.), a new and emerging, yield-limiting disease in the United States. Since being first reported in Illinois and Indiana in 2015, P. maydis can now be found across much of the corn growing regions of the United States. Knowledge of the epidemiology of P. maydis is limited but could be useful in developing tar spot prediction tools. The research presented here aims to elucidate the environmental conditions necessary for the development of tar spot in the field and the creation of predictive models to anticipate future tar spot epidemics. Extended periods (30-day windowpanes) of moderate mean ambient temperature (18–23 °C) were most significant for explaining the development of tar spot. Shorter periods (14- to 21-day windowpanes) of moisture (relative humidity, dew point, number of hours with predicted leaf wetness) were negatively correlated with tar spot development. These weather variables were used to develop multiple logistic regression models, an ensembled model, and two machine learning models for the prediction of tar spot development. This work has improved the understanding of P. maydis epidemiology and provided the foundation for the development of a predictive tool for anticipating future tar spot epidemics.

In this study, four recombinant inbred line (RIL) soybean populations were screened for their response to infection by Pythium sylvaticum , Pythium irregulare , Pythium oopapillum , and Pythium torulosum. The parents, PI 424237A, PI 424237B, PI 408097, and PI 408029, had higher levels of resistance to these species in a preliminary screening and were crossed with “Williams,” a susceptible cultivar. A modified seed rot assay was used to evaluate RIL populations for their response to specific Pythium species selected for a particular population based on preliminary screenings. Over 2500 single-nucleotide polymorphism (SNP) markers were used to construct chromosomal maps to identify regions associated with resistance to Pythium species. Several minor and large effect quantitative disease resistance loci (QDRL) were identified including one large effect QDRL on chromosome 8 in the population of PI 408097 × Williams. It was identified by two different disease reaction traits in P. sylvaticum , P. irregulare , and P. torulosum . Another large effect QDRL was identified on chromosome 6 in the population of PI 408029 × Williams, and conferred resistance to P. sylvaticum and P. irregulare . These large effect QDRL will contribute toward the development of improved soybean cultivars with higher levels of resistance to these common soil-borne pathogens.

Clavibacter michiganensis subsp. nebraskensis (Cmn), the causal organism of Goss's wilt and leaf blight of maize, can be detected in the phyllosphere of its host prior to disease development. We compared the morphology and pathogenicity of 37 putative isolates of Cmn recovered from asymptomatic and symptomatic maize leaves. Thirty-three of the isolates produced mucoid orange colonies, irrespective of the source of isolation and all but four of these isolates were pathogenic on maize. The remaining 4 isolates recovered from asymptomatic leaves had large fluidal yellow colonies, and were non-pathogenic on maize. Isolates varied in their aggressiveness on a susceptible hybrid of maize but no significant differences in aggressiveness were detected between epiphytic isolates and those recovered from diseased maize tissues. The genomics of Cmn is poorly understood; therefore as a first step to determining what genes may play a role in virulence, we compared 33 putative virulence gene sequences from 6 pathogenic and a non-pathogenic isolate recovered from the phyllosphere. Sequence polymorphisms were detected in 5 genes, cellulase A, two endoglucanases, xylanase B and a pectate lyase but there was no relationship with pathogenicity. Further research is needed to determine what genes play a role in virulence of Cmn. Our data show however, that the virulence factors in Cmn likely differ from those reported for the closely related subspecies michiganensis and sepedonicus.

Goss's wilt, caused by the Gram-positive actinobacterium Clavibacter nebraskensis, is an important bacterial disease of maize. The molecular and genetic mechanisms of resistance to the bacterium, or, in general, Gram-positive bacteria causing plant diseases, remain poorly understood. Here, we examined the genetic basis of Goss's wilt through differential gene expression, standard genome-wide association mapping (GWAS), extreme phenotype (XP) GWAS using highly resistant (R) and highly susceptible (S) lines, and quantitative trait locus (QTL) mapping using 3 bi-parental populations, identifying 11 disease association loci. Three loci were validated using near-isogenic lines or recombinant inbred lines. Our analysis indicates that Goss's wilt resistance is highly complex and major resistance genes are not commonly present. RNA sequencing of samples separately pooled from R and S lines with or without bacterial inoculation was performed, enabling identification of common and differential gene responses in R and S lines. Based on expression, in both R and S lines, the photosynthesis pathway was silenced upon infection, while stress-responsive pathways and phytohormone pathways, namely, abscisic acid, auxin, ethylene, jasmonate, and gibberellin, were markedly activated. In addition, 65 genes showed differential responses (up- or down-regulated) to infection in R and S lines. Combining genetic mapping and transcriptional data, individual candidate genes conferring Goss's wilt resistance were identified. Collectively, aspects of the genetic architecture of Goss's wilt resistance were revealed, providing foundational data for mechanistic studies.

The genus Phyllachora contains numerous obligate fungal parasites that produce raised, melanized structures called stromata on their plant hosts referred to as tar spot. Members of this genus are known to infect many grass species but generally do not cause significant damage or defoliation, with the exception of P. maydis which has emerged as an important pathogen of maize throughout the Americas, but the origin of this pathogen remains unknown. To date, species designations for Phyllachora have been based on host associations and morphology, and most species are assumed to be host specific. We assessed the sequence diversity of 186 single stroma isolates collected from 16 hosts representing 15 countries. Samples included both herbarium and contemporary strains that covered a temporal range from 1905 to 2019. These 186 isolates were grouped into five distinct species with strong bootstrap support. We found three closely related, but genetically distinct groups of Phyllachora are capable of infecting maize in the United States, we refer to these as the P. maydis species complex. Based on herbarium specimens, we hypothesize that these three groups in the P. maydis species complex originated from Central America, Mexico, and the Caribbean. Although two of these groups were only found on maize, the third and largest group contained contemporary strains found on maize and other grass hosts, as well as herbarium specimens from maize and other grasses that include 10 species of Phyllachora. The herbarium specimens were previously identified based on morphology and host association. This work represents the first attempt at molecular characterization of Phyllachora species infecting grass hosts and indicates some Phyllachora species can infect a broad range of host species and there may be significant synonymy in the Phyllachora genus. Signs and symptoms of Phyllachora spp. on grasses. Phyllachora maydis on maize at severe levels (a); with ascospores being extruded from stroma (b) and showing characteristic tapering ends of mature stromata (c). Phyllachora spp. on Elymus in Michigan (d), Fall Ryegrass in Illinois, and an unidentified grass in Indiana (f). Photo credit N. Kleczewski

Phytophthora sojae causes Phytophthora root and stem rot of soybean and has been primarily managed through deployment of qualitative Resistance to P. sojae genes (Rps genes). The effectiveness of each individual or combination of Rps gene(s) depends on the diversity and pathotypes of the P. sojae populations present. Due to the complex nature of P. sojae populations, identification of more novel Rps genes is needed. In this study, phenotypic data from previous studies of 16 panels of plant introductions (PIs) were analyzed. Panels 1 and 2 consisted of 448 Glycine max and 520 G. soja, which had been evaluated for Rps gene response with a combination of P. sojae isolates. Panels 3 and 4 consisted of 429 and 460 G. max PIs, respectively, which had been evaluated using individual P. sojae isolates with complex virulence pathotypes. Finally, Panels 5–16 (376 G. max PIs) consisted of data deposited in the USDA Soybean Germplasm Collection from evaluations with 12 races of P. sojae. Using these panels, genome‐wide association (GWA) analyses were carried out by combining phenotypic and SoySNP50K genotypic data. GWA models identified two, two, six, and seven novel Rps loci with Panels 1, 2, 3, and 4, respectively. A total of 58 novel Rps loci were identified using Panels 5–16. Genetic and phenotypic dissection of these loci may lead to the characterization of novel Rps genes that can be effectively deployed in new soybean cultivars against diverse P. sojae populations.