Comparative transcriptomics of soybean genotypes with partial resistance towards Phytophthora sojae, Conrad, and M92-220, to moderately susceptible fast neutron mutant soybeans and Sloan.

The breeding of disease-resistant soybeans cultivars to manage Phytophthora root and stem rot caused by the pathogen Phytophthora sojae involves combining quantitative disease resistance (QDR) and Rps gene-mediated resistance. To identify and confirm potential mechanisms of QDR towards P. sojae, we conducted a time course study comparing changes in gene expression among Conrad and M92-220 with high QDR to susceptible genotypes, Sloan and 3 mutants derived from fast neutron (FN) irradiation of M92-220. Differentially expressed genes from Conrad and M92-220 indicated several shared defense-related pathways at the transcriptomic level, but also defense pathways unique to each cultivar such as stilbenoid, diarylheptanoid and gingerol biosynthesis, and monobactam biosynthesis. Gene Ontology pathway analysis showed that the susceptible FN mutants lacked enrichment of three terpenoid related-pathways and two cell wall-related pathways at either one or both timepoints, in contrast to M92-220. The susceptible mutants also lacked enrichment of potentially important KEGG pathways at either one or both timepoints, including sesquiterpenoid and triterpenoid biosynthesis, thiamine metabolism, arachidonic acid, stilbenoid, diarylheptanoid and gingerol biosynthesis, and monobactam biosynthesis. Additionally, thirty-one genes which were differentially expressed in M92-220 following P. sojae infection were not expressed in the mutants. These 31 genes have annotations related to unknown proteins, valine, leucine, and isoleucine biosynthesis and protein and lipid metabolic processes. The results of this study confirm previously proposed mechanisms of QDR, provide evidence for potential novel QDR pathways in M92-220, and furthers our understanding of the complex network associated with QDR mechanisms in soybean towards P. sojae.

Open Access and Reproducibility in Plant Pathology Research: Guidelines and Best Practices.

The landscape of scientific publishing is experiencing a transformative shift toward open access, a paradigm that mandates the availability of research outputs such as data, code, materials, and publications. Open access provides increased reproducibility and allows for reuse of these resources. This article provides guidance for best publishing practices of scientific research, data, and associated resources, including code, in The American Phytopathological Society journals. Key areas such as diagnostic assays, experimental design, data sharing, and code deposition are explored in detail. This guidance aligns with that observed by other leading journals. We hope the information assembled in this paper will raise awareness of best practices and enable greater appraisal of the true effects of biological phenomena in plant pathology.

Picarbutrazox effectiveness added to a seed treatment mixture for management of Oomycetes that impact soybean in Ohio.

None of the current oomycota fungicides are effective towards all species of Phytophthora, Phytopythium, Globisporangium, and Pythium that affect soybean seed and seedlings in Ohio. Picarbutrazox is a new oomyceticide with a novel mode of action towards Oomycete pathogens. Our objectives were to evaluate picarbutrazox to determine i) baseline sensitivity (EC50) to 189 isolates of 29 species, ii) the efficacy with a base seed treatment with three cultivars with different levels of resistance in 14 field environments; and iii) if the rhizosphere microbiome was affected by the addition of the seed treatment on a moderately susceptible cultivar. The mycelial growth of all isolates was inhibited beginning at 0.001µg and the EC50 ranged from 0.0013 to 0.0483 µg a.i. ml-1. The effect of seed treatment was significantly different for plant population and yield in 8 of 14 and 6 of 12 environments, respectively. The addition of picarbutrazox at 1 and 2.5 g a.i. 100 kg seed-1 to the base seed treatment compared to the base alone was associated with higher plant populations and yield in 3 and 1 environment, respectively. There was limited impact of the seed treatment mefenoxam 7.5 g a.i. plus picarbutrazox 1 g a.i. per 100 kg seed-1 on the oomycetes detected in the rhizosphere of soybean seedlings collected at the V1 growth stage. Picarbutrazox has efficacy towards a wider range of oomycetes that cause disease on soybean and this will be another oomyceticide tool to combat early season damping-off in areas where environmental conditions highly favor disease development.

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach.

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance.

Interactions Among Heterodera glycines, Macrophomina phaseolina, and Soybean Genotype.

Heterodera glycines, the soybean cyst nematode (SCN), and fungal pathogen Macrophomina phaseolina are economically important soybean pathogens that may coinfest fields. Resistance remains the most effective management tactic for SCN, and the rhg1-b resistance allele derived from plant introduction 88788 is most commonly deployed in the northern United States. The concomitant effects of SCN and M. phaseolina on soybean performance, as well as the effect of the rhg1-b allele in two different genetic backgrounds, were evaluated in three environments (during 2013 to 2015) and a greenhouse bioassay. Within two soybean populations, half of the lines had the rhg1-b allele, and the other half had the susceptible allele in the backgrounds of the cultivars IA3023 and LD00-3309. Significant interactions between soybean rhg1-b allele and M. phaseolina-infested plots were observed in 2014. In all experiments, initial SCN populations (Pi) and M. phaseolina in roots were associated with reduced soybean yield. SCN reproduction factor (RF = final population/Pi) was affected by SCN Pi, rhg1-b, and genetic background. A background-by-genotype interaction on yield was observed only in 2015, with a stronger rhg1-b effect in the LD00-3309 background, which suggested that the susceptible parent 'IA3023' is tolerant to SCN. SCN female index from greenhouse experiments was compared with field RF, and Lin's concordance and Pearson's correlation coefficients decreased with increasing field SCN Pi in soil. In this study, both SCN and M. phaseolina reduced soybean yield asymptomatically, and the impact of SCN rhg1-b resistance was dependent on SCN virulence but also population density.

Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae.

Phytophthora root and stem rot is a yield-limiting soybean disease caused by the soil-borne oomycete Phytophthora sojae. Although multiple quantitative disease resistance loci (QDRL) have been identified, most explain <10% of the phenotypic variation (PV). The major QDRL explaining up to 45% of the PV were previously identified on chromosome 18 and represent a valuable source of resistance for soybean breeding programs. Resistance alleles from plant introductions 427105B and 427106 significantly increase yield in disease-prone fields and result in no significant yield difference in fields with less to no disease pressure. In this study, high-resolution mapping reduced the QDRL interval to 3.1 cm, and RNA-seq analysis of near-isogenic lines (NILs) varying at QDRL-18 pinpointed a single gene of interest which was downregulated in inoculated NILs carrying the resistant allele compared to inoculated NILs with the susceptible allele. This gene of interest putatively encodes a serine-threonine kinase (STK) related to the AtCR4 family and may be acting as a susceptibility factor, based on the specific increase of jasmonic acid concentration in inoculated NILs. This work facilitates further functional analyses and marker-assisted breeding efforts by prioritizing candidate genes and narrowing the targeted region for introgression.

Giant Starship Elements Mobilize Accessory Genes in Fungal Genomes.

Accessory genes are variably present among members of a species and are a reservoir of adaptive functions. In bacteria, differences in gene distributions among individuals largely result from mobile elements that acquire and disperse accessory genes as cargo. In contrast, the impact of cargo-carrying elements on eukaryotic evolution remains largely unknown. Here, we show that variation in genome content within multiple fungal species is facilitated by Starships, a newly discovered group of massive mobile elements that are 110 kb long on average, share conserved components, and carry diverse arrays of accessory genes. We identified hundreds of Starship-like regions across every major class of filamentous Ascomycetes, including 28 distinct Starships that range from 27 to 393 kb and last shared a common ancestor ca. 400 Ma. Using new long-read assemblies of the plant pathogen Macrophomina phaseolina, we characterize four additional Starships whose activities contribute to standing variation in genome structure and content. One of these elements, Voyager, inserts into 5S rDNA and contains a candidate virulence factor whose increasing copy number has contrasting associations with pathogenic and saprophytic growth, suggesting Voyager's activity underlies an ecological trade-off. We propose that Starships are eukaryotic analogs of bacterial integrative and conjugative elements based on parallels between their conserved components and may therefore represent the first dedicated agents of active gene transfer in eukaryotes. Our results suggest that Starships have shaped the content and structure of fungal genomes for millions of years and reveal a new concerted route for evolution throughout an entire eukaryotic phylum.

Oxathiapiprolin Alone or Mixed with Metalaxyl Seed Treatment for Management of Soybean Seedling Diseases Caused by Species of Phytophthora, Phytopythium, and Pythium.

Species of Phytophthora, Phytopythium, and Pythium affect soybean seed and seedlings each year, primarily through reduced plant populations and yield. Oxathiapiprolin is effective at managing several foliar diseases caused by some oomycetes. The objectives of these studies were to evaluate oxathiapiprolin in a discriminatory dose assay in vitro; evaluate oxathiapiprolin as a soybean seed treatment on a moderately susceptible cultivar in 10 environments; compare the impact of seed treatment on plant populations and yields in environments with low and high precipitation; and compare a seed treatment mixture on cultivars with different levels of resistance in four environments. There was no reduction in growth in vitro among 13 species of Pythium at 0.1 µg ml-1. Soybean seed treated with the base fungicide plus oxathiapiprolin (12 and 24 µg a.i. seed-1) alone, oxathiapiprolin (12 µg a.i. seed-1) plus mefenoxam (6 µg a.i. seed-1), or oxathiapiprolin (24 µg a.i. seed-1) plus ethaboxam (12.1 µg a.i. seed-1) had greater yields in environments that received ≥50 mm of precipitation within 14 days after planting compared with those that received less. Early plant population and yield were significantly higher for seed treated with oxathiapiprolin (24 µg a.i. seed-1) + metalaxyl (13.2 µg a.i. seed-1) compared with nontreated for six of seven cultivars in at least one of four environments. Oxathiapiprolin combined with another Oomycota fungicide applied to seed has the potential to be used to protect soybean plant establishment and yield in regions prone to poor drainage after high levels of precipitation.

Pathotype Complexity and Genetic Characterization of Phytophthora sojae Populations in Illinois, Indiana, Kentucky, and Ohio.

Phytophthora sojae, the causal agent of Phytophthora root and stem rot of soybean, has been managed with single Rps genes since the 1960s but has subsequently adapted to many of these resistance genes, rendering them ineffective. The objective of this study was to examine the pathotype and genetic diversity of P. sojae from soil samples across Illinois, Indiana, Kentucky, and Ohio by assessing which Rps genes were still effective and identifying possible population clusters. There were 218 pathotypes identified from 473 P. sojae isolates with an average of 6.7 out of 15 differential soybean lines exhibiting a susceptible response for each isolate. Genetic characterization of 103 P. sojae isolates from across Illinois, Indiana, Kentucky, and Ohio with 19 simple sequence repeat markers identified 92 multilocus genotypes. There was a moderate level of population differentiation between these four states, with pairwise FST values ranging from 0.026 to 0.246. There were also moderate to high levels of differentiation between fields, with pairwise FST values ranging from 0.071 to 0.537. Additionally, cluster analysis detected the presence of P. sojae population structure across neighboring states. The level of pathotype and genetic diversity, in addition to the identification of population clusters, supports the hypothesis of occasional outcrossing events that allow an increase in diversity and the potential to select for a loss in avirulence to specific resistance genes within regions. The trend of suspected gene flow among neighboring fields is expected to be an ongoing issue with current agricultural practices.

Identification of Quantitative Disease Resistance Loci Toward Four Pythium Species in Soybean.

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.

Mining germplasm panels and phenotypic datasets to identify loci for resistance to Phytophthora sojae in soybean.

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.

Testing methods and statistical models of genomic prediction for quantitative disease resistance to Phytophthora sojae in soybean [Glycine max (L.) Merr] germplasm collections.

KEY MESSAGE: Genomic prediction of quantitative resistance toward Phytophthora sojae indicated that genomic selection may increase breeding efficiency. Statistical model and marker set had minimal effect on genomic prediction with > 1000 markers. Quantitative disease resistance (QDR) toward Phytophthora sojae in soybean is a complex trait controlled by many small-effect loci throughout the genome. Along with the technical and rate-limiting challenges of phenotyping resistance to a root pathogen, the trait complexity can limit breeding efficiency. However, the application of genomic prediction to traits with complex genetic architecture, such as QDR toward P. sojae, is likely to improve breeding efficiency. We provide a novel example of genomic prediction by measuring QDR to P. sojae in two diverse panels of more than 450 plant introductions (PIs) that had previously been genotyped with the SoySNP50K chip. This research was completed in a collection of diverse germplasm and contributes to both an initial assessment of genomic prediction performance and characterization of the soybean germplasm collection. We tested six statistical models used for genomic prediction including Bayesian Ridge Regression; Bayesian LASSO; Bayes A, B, C; and reproducing kernel Hilbert spaces. We also tested how the number and distribution of SNPs included in genomic prediction altered predictive ability by varying the number of markers from less than 50 to more than 34,000 SNPs, including SNPs based on sequential sampling, random sampling, or selections from association analyses. Predictive ability was relatively independent of statistical model and marker distribution, with a diminishing return when more than 1000 SNPs were included in genomic prediction. This work estimated relative efficiency per breeding cycle between 0.57 and 0.83, which may improve the genetic gain for P. sojae QDR in soybean breeding programs.

Auxin Profiling and GmPIN Expression in Phytophthora sojae-Soybean Root Interactions.

Auxin (indole-3-acetic acid, IAA) has been implicated as a susceptibility factor in both beneficial and pathogenic molecular plant-microbe interactions. Previous studies have identified a large number of auxin-related genes underlying quantitative disease resistance loci (QDRLs) for Phytophthora sojae. Thus, we hypothesized that auxin may be involved the P. sojae-soybean interaction. The levels of IAA and related metabolites were measured in mycelia and media supernatant as well as in mock and inoculated soybean roots in a time course assay. The expression of 11 soybean Pin-formed (GmPIN) auxin efflux transporter genes was also examined. Tryptophan, an auxin precursor, was detected in the P. sojae mycelia and media supernatant. During colonization of roots, levels of IAA and related metabolites were significantly higher in both moderately resistant Conrad and moderately susceptible Sloan inoculated roots compared with mock controls at 48 h postinoculation (hpi) in one experiment and at 72 hpi in a second, with Sloan accumulating higher levels of the auxin catabolite IAA-Ala than Conrad. Additionally, one GmPIN at 24 hpi, one at 48 hpi, and three at 72 hpi had higher expression in inoculated compared with the mock control roots in Conrad. The ability of resistant cultivars to cope with auxin accumulation may play an important role in quantitative disease resistance. Levels of jasmonic acid (JA), another plant hormone associated with defense responses, were also higher in inoculated roots at these same time points, suggesting that JA also plays a role during the later stages of infection.

Resistance of the SoyNAM Parents to Seed and Root Rot Caused by Four Pythium Species.

Some Pythium spp. cause damping off and root rot in soybeans and other crop species. One of the most effective management tools to reduce disease is host resistance; however, little is known about resistance in soybean to Pythium spp. The soybean nested associated mapping (SoyNAM) parent lines are a set of germplasms that were crossed to a single hub parent to create recombinant inbred line populations for the purpose of mapping agronomic traits. The SoyNAM parents were screened for resistance to Pythium lutarium, Pythium oopapillum, Pythium sylvaticum, and Pythium torulosum in separate assays to evaluate seed and root rot severity. Of the 40 SoyNAM parents, only 'Maverick' was resistant to the four species tested; however, 13 were resistant to three species. Other lines were resistant to two, one, or none of the species tested. Correlations between seed and root rot severity for the lines assessed were weak or insignificant. Results indicate that mechanisms of resistance to seed and root rot caused by Pythium spp. may not necessarily be the same.

Genome-wide association analyses of quantitative disease resistance in diverse sets of soybean [Glycine max (L.) Merr.] plant introductions.

Phytophthora sojae is one of the costliest soybean pathogens in the US. Quantitative disease resistance (QDR) is a vital part of Phytophthora disease management. In this study, QDR was measured in 478 and 495 plant introductions (PIs) towards P. sojae isolates OH.121 and C2.S1, respectively, in genome-wide association (GWA) analyses to identify genetic markers linked to QDR loci (QDRL). Populations were generated by sampling PIs from the US, the Republic of Korea, and the full collection of PIs maintained by the USDA. Additionally, a meta-analysis of QDRL reported from bi-parental studies was done to compare past and present findings. Twenty-four significant marker-trait associations were identified from the 478 PIs phenotyped with OH.121, and an additional 24 marker-trait associations were identified from the 495 PIs phenotyped with C2.S1. In total, 48 significant markers were distributed across 16 chromosomes and based on linkage analysis, represent a total of 44 QDRL. The majority of QDRL were identified with only one of the two isolates, and only a region on chromosome 13 was consistently identified. Regions on chromosomes 3, 13, and 17 were identified in previous GWA-analyses and were re-identified in this study. Five QDRL co-localized with P. sojae meta-QDRL identified from QDRL reported in previous biparental mapping studies. The remaining regions represent novel QDRL, in the soybean-P. sojae pathosystem and were primarily identified in germplasm from the Republic of Korea. Overall, the number of loci identified in this study highlights the complexity of QDR to P. sojae.

The Efficacy of Ethaboxam as a Soybean Seed Treatment Toward Phytophthora, Phytopythium, and Pythium in Ohio.

Phytophthora, Phytopythium, and Pythium species that cause early-season seed decay and pre-emergence and post-emergence damping off of soybean are most commonly managed with seed treatments. The phenylamide fungicides metalaxyl and mefenoxam, and ethaboxam are effective toward some but not all species. The primary objective of this study was to evaluate the efficacy of ethaboxam in fungicide mixtures and compare those with other fungicides as seed treatments to protect soybean against Pythium, Phytopythium, and Phytophthora species in both high-disease field environments and laboratory seed plate assays. The second objective was to evaluate these seed treatment mixtures on cultivars that have varying levels and combinations of resistance to these soilborne pathogens. Five of eight environments received adequate precipitation in the 14 days after planting for high levels of seedling disease development and treatment evaluations. Three environments had significantly greater stands, and three had significantly greater yield when ethaboxam was used in the seed treatment mixture compared with treatments containing metalaxyl or mefenoxam alone. Three fungicide formulations significantly reduced disease severity compared with nontreated in the seed plate assay for 17 species. However, the combination of ethaboxam plus metalaxyl in a mixture was more effective than either fungicide alone against some Pythium and Phytopythium species. Overall, our results indicate that the addition of ethaboxam to a fungicide seed treatment is effective in reducing seed rot caused by these pathogens commonly isolated from soybean in Ohio but that these effects can be masked when cultivars with resistance are planted.

Soybean seed treatment: how do fungicides translocate in plants?

BACKGROUND: Soybean seed treatment with fungicides is a well-established disease management strategy. However, the movement of these fungicides within seedlings is not always well characterized. Thus, the objectives of this study were to determine the pattern of translocation of three fungicides with different modes of action applied as a seed treatment, and the effect of soil type on translocation. RESULTS: Most of the absorbed radioactivity was concentrated in the cotyledons and the maximum sum of the rates of absorption by roots, stems, and leaves of the plants was 15%. In most cases, absorption by roots, stems, and leaves were lower than 5% for 14 C-pyraclostrobin and 14 C-metalaxyl, and 1.6% for 14 C-carbendazim. Fungicides absorbed by the roots and the whole seedlings were higher when plants were grown in soil with lower organic matter content. Fungicides in the cotyledons are unlikely to be redistributed and are lost when cotyledons fall off the plants. CONCLUSION: Cotyledons are the part of the plant where fungicides are most absorbed, regardless of the fungicide. Soil type affects the absorption of fungicides, and in this study it was most likely caused by soil organic matter. These data improve knowledge of the movement of seed treatment fungicides in soybean seedlings and may help the development of seed treatment chemistry to manage seed and soilborne pathogens.

Genetic Structure of Rhizoctonia solani AG-2-2IIIB from Soybean in Illinois, Ohio, and Ontario.

Rhizoctonia solani AG-2-2IIIB is an important seedling pathogen of soybean in North America and other soybean-growing regions around the world. There is no information regarding the population genetics of field populations of R. solani associated with soybean seedling disease. More specifically, information regarding genetic diversity, the mode of reproduction, and the evolutionary factors that shape different R. solani populations separated in time and space are lacking. We exploited genotyping by sequencing as a tool to assess the genetic structure of R. solani AG-2-2IIIB populations from Illinois, Ohio, and Ontario and investigate the reproductive mode of this subgroup. Our results revealed differences in genotypic diversity among three populations, with the Ontario population having greatest diversity. An overrepresentation of multilocus genotypes (MLGs) and a rejection of the null hypothesis of random mating in all three populations suggested clonality within each population. However, phylogenetic analysis revealed long terminal multifurcating branches for most members of the Ontario population, suggesting a mixed reproductive mode for this population. Analysis of molecular variance revealed low levels of population differentiation, and sharing of similar MLGs among populations highlights the role of genotype flow as an evolutionary force shaping population structure of this subgroup.

Hybrid Genome Assembly of a Major Quantitative Disease Resistance Locus in Soybean Toward Fusarium graminearum.

Schwabe [teleomorph: Gibberella zeae (Schweintiz) Petch] has been identified as a pathogen of soybean [ (L.) Merr.] causing seed, seedling damping-off and root rot in North America. A major quantitative disease resistance locus (QDRL) that contributed 38.5% of the phenotypic variance toward in soybean was previously identified through mapping of a recombinant inbred line (RIL) population derived from a cross between 'Wyandot' and PI 567301B. This major QDRL mapped to chromosome 8 to a predicted 305 kb region harboring 36 genes. This locus maps near the locus for soybean cyst nematode (SCN) and the locus contributing to seed coat color. Long-read sequencing of the region was completed and variations in gene sequence and gene order compared with the 'Williams 82' reference were identified. Molecular markers were developed for genes within this region and mapped in the original population, slightly narrowing the region of interest. Analyses of the hybrid genome reassembly using three previously published bacterial artificial chromosome (BAC) sequences (BAC56G2, BAC104J7, and BAC77G7-a) combined with RNA-sequencing narrowed the region making candidate gene identification possible. The markers within this region may be used for marker-assisted selection (MAS). There were 10 differentially expressed genes between resistant and susceptible lines, with four of these candidates also located within the genomic interval defined by the flanking markers. These genes included an actin-related protein 2/3 complex subunit, an unknown protein, a hypothetical protein, and a chalcone synthase 3.

Molecular characterization of genomic regions for resistance to Pythium ultimum var. ultimum in the soybean cultivar Magellan.

KEY MESSAGE: Two novel QTL for resistance to Pythium ultimum var. ultimum were identified in soybean using an Illumina SNP Chip and whole genome re-sequencing. Pythium ultimum var. ultimum is one of numerous Pythium spp. that causes severe pre- and post-emergence damping-off of seedlings and root rot of soybean [Glycine max (L.) Merr.]. The objective of this research was to identify quantitative trait loci (QTL) for resistance to P. ultimum var. ultimum in a recombinant inbred line population derived from a cross of 'Magellan' (moderately resistant) and PI 438489B (susceptible). Two different mapping approaches were utilized: the universal soybean linkage panel (USLP 1.0) and the bin map constructed from whole genome re-sequencing (WGRS) technology. Two genomic regions associated with variation in three disease-related parameters were detected using both approaches, with the bin map providing higher resolution. Using WGRS, the first QTL were mapped within a 350-kbp region on Chr. 6 and explained 7.5-13.5% of the phenotypic variance. The second QTL were positioned in a 260-kbp confidence interval on Chr. 8 and explained 6.3-16.8% of the phenotypic variation. Candidate genes potentially associated with disease resistance were proposed. High-resolution genetic linkage maps with a number of significant SNP markers could benefit marker-assisted breeding and dissection of the molecular mechanisms underlying soybean resistance to Pythium damping-off in 'Magellan.' Additionally, the outputs of this study may encourage more screening of diverse soybean germplasm and utilization of genome-wide association studies to understand the genetic basis of quantitative disease resistance.