Main and epistatic QTL analyses for Sclerotinia Head Rot resistance in sunflower

Population and genome-wide association studies of Sclerotinia sclerotiorum isolates collected from diverse host plants throughout the United States

Introduction

Sclerotinia sclerotiorum is a necrotrophic fungal pathogen causing disease and economic loss on numerous crop plants. This fungus has a broad host range and can infect over 400 plant species, including important oilseed crops such as soybean, canola, and sunflower. S. sclerotiorum isolates vary in aggressiveness of lesion formation on plant tissues. However, the genetic basis for this variation remains to be determined. The aims of this study were to evaluate a diverse collection of S. sclerotiorum isolates collected from numerous hosts and U.S. states for aggressiveness of stem lesion formation on sunflower, to evaluate the population characteristics, and to identify loci associated with isolate aggressiveness using genome-wide association mapping.

Methods

A total of 219 S. sclerotiorum isolates were evaluated for stem lesion formation on two sunflower inbred lines and genotyped using genotyping-by-sequencing. DNA markers were used to assess population differentiation across hosts, regions, and climatic conditions and to perform a genome-wide association study of isolate aggressiveness.

Results and discussion

We observed a broad range of aggressiveness for lesion formation on sunflower stems, and only a moderate correlation between aggressiveness on the two lines. Population genetic evaluations revealed differentiation between populations from warmer climate regions compared to cooler regions. Finally, a genome-wide association study of isolate aggressiveness identified three loci significantly associated with aggressiveness on sunflower. Functional characterization of candidate genes at these loci will likely improve our understanding of the virulence strategies used by this pathogen to cause disease on a wide array of agriculturally important host plants.

Co-Expression Networks in Sunflower: Harnessing the Power of Multi-Study Transcriptomic Public Data to Identify and Categorize Candidate Genes for Fungal Resistance

Fungal plant diseases are a major threat to food security worldwide. Current efforts to identify and list loci involved in different biological processes are more complicated than originally thought, even when complete genome assemblies are available. Despite numerous experimental and computational efforts to characterize gene functions in plants, about ~40% of protein-coding genes in the model plant Arabidopsis thaliana L. are still not categorized in the Gene Ontology (GO) Biological Process (BP) annotation. In non-model organisms, such as sunflower (Helianthus annuus L.), the number of BP term annotations is far fewer, ~22%. In the current study, we performed gene co-expression network analysis using eight terabytes of public transcriptome datasets and expression-based functional prediction to categorize and identify loci involved in the response to fungal pathogens. We were able to construct a reference gene network of healthy green tissue (GreenGCN) and a gene network of healthy and stressed root tissues (RootGCN). Both networks achieved robust, high-quality scores on the metrics of guilt-by-association and selective constraints versus gene connectivity. We were able to identify eight modules enriched in defense functions, of which two out of the three modules in the RootGCN were also conserved in the GreenGCN, suggesting similar defense-related expression patterns. We identified 16 WRKY genes involved in defense related functions and 65 previously uncharacterized loci now linked to defense response. In addition, we identified and classified 122 loci previously identified within QTLs or near candidate loci reported in GWAS studies of disease resistance in sunflower linked to defense response. All in all, we have implemented a valuable strategy to better describe genes within specific biological processes.

A Mechanistic Model Accounting for the Effect of Soil Moisture, Weather, and Host Growth Stage on the Development of Sclerotinia sclerotiorum

The fungus Sclerotinia sclerotiorum causes serious losses to several agricultural crops worldwide. By using systems analysis, we retrieved the available knowledge concerning S. sclerotiorum from the literature and then analyzed and synthesized the data to develop a mechanistic, dynamic, weather-driven model for the prediction of epidemics on different crops. The model accounts for i) the production and survival of apothecia; ii) the production, dispersal, and survival of ascospores; iii) infection by ascospores; and iv) lesion onset. The ability of the model to predict the occurrence of apothecia was evaluated for epidemics observed with different climates, soil types, and host crops (soybean, white bean, and carrot) using independent data obtained from trials conducted in Ontario (Canada) in 1981, 1982, and from 1999 to 2002; in Michigan (U.S.A.) in 2015 and 2016; and in Wisconsin (U.S.A.) in 2016. The model showed 0.82 accuracy and 0.73 specificity in predicting the presence of apothecia, with a posterior probability of correctly predicting apothecia to be present or absent of 0.804 and 0.876, respectively. The model was also validated for its ability to predict disease progress on soybean and sunflower in Ontario in 1981 and 1982, in Manitoba (Canada) in 2001 and 2002, and in Michigan in 2015 and 2016. Comparison of model output with observations showed a concordance correlation coefficient of 0.948, and a root mean square error of 0.122. The model represents an improvement of previous S. sclerotiorum models and could be useful for making decisions on disease control.

Genome-Wide Association Studies in Sunflower: Towards Sclerotinia sclerotiorum and Diaporthe/Phomopsis Resistance Breeding

Diseases caused by necrotrophic fungi, such as the cosmopolitan Sclerotinia sclerotiorum and the Diaporthe/Phomopsis complex, are among the most destructive diseases of sunflower worldwide. The lack of complete resistance combined with the inefficiency of chemical control makes assisted breeding the best strategy for disease control. In this work, we present an integrated genome-wide association (GWA) study investigating the response of a diverse panel of sunflower inbred lines to both pathogens. Phenotypic data for Sclerotinia head rot (SHR) consisted of five disease descriptors (disease incidence, DI; disease severity, DS; area under the disease progress curve for DI, AUDPCI, and DS, AUDPCS; and incubation period, IP). Two disease descriptors (DI and DS) were evaluated for two manifestations of Diaporthe/Phomopsis: Phomopsis stem canker (PSC) and Phomopsis head rot (PHR). In addition, a principal component (PC) analysis was used to derive transformed phenotypes as inputs to a univariate GWA (PC-GWA). Genotypic data comprised a panel of 4269 single nucleotide polymorphisms (SNP), generated via genotyping-by-sequencing. The GWA analysis revealed 24 unique marker-trait associations for SHR, 19 unique marker-trait associations for Diaporthe/Phomopsis diseases, and 7 markers associated with PC1 and PC2. No common markers were found for the response to the two pathogens. Nevertheless, epistatic interactions were identified between markers significantly associated with the response to S. sclerotiorum and Diaporthe/Phomopsis. This suggests that, while the main determinants of resistance may differ for the two pathogens, there could be an underlying common genetic basis. The exploration of regions physically close to the associated markers yielded 364 genes, of which 19 were predicted as putative disease resistance genes. This work presents the first simultaneous evaluation of two manifestations of Diaporthe/Phomopsis in sunflower, and undertakes a comprehensive GWA study by integrating PSC, PHR, and SHR data. The multiple regions identified, and their exploration to identify candidate genes, contribute not only to the understanding of the genetic basis of resistance, but also to the development of tools for assisted breeding.

The evolutionary and molecular features of the broad-host-range plant pathogen Sclerotinia sclerotiorum

Sclerotinia sclerotiorum is a pathogenic fungus that infects hundreds of plant species, including many of the world's most important crops. Key features of S. sclerotiorum include its extraordinary host range, preference for dicotyledonous plants, relatively slow evolution, and production of protein effectors that are active in multiple host species. Plant resistance to this pathogen is highly complex, typically involving numerous polymorphisms with infinitesimally small effects, which makes resistance breeding a major challenge. Due to its economic significance, S. sclerotiorum has been subjected to a large amount of molecular and evolutionary research. In this updated pathogen profile, we review the evolutionary and molecular features of S. sclerotiorum and discuss avenues for future research into this important species.

A Quantitative Genetic Study of Sclerotinia Head Rot Resistance Introgressed from the Wild Perennial Helianthus maximiliani into Cultivated Sunflower (Helianthus annuus L.)

Sclerotinia head rot (HR), caused by Sclerotinia sclerotiorum, is an economically important disease of sunflower with known detrimental effects on yield and quality in humid climates worldwide. The objective of this study was to gain insight into the genetic architecture of HR resistance from a sunflower line HR21 harboring HR resistance introgressed from the wild perennial Helianthus maximiliani. An F2 population derived from the cross of HA 234 (susceptible-line)/HR21 (resistant-line) was evaluated for HR resistance at two locations during 2019−2020. Highly significant genetic variations (p < 0.001) were observed for HR disease incidence (DI) and disease severity (DS) in both individual and combined analyses. Broad sense heritability (H2) estimates across environments for DI and DS were 0.51 and 0.62, respectively. A high-density genetic map of 1420.287 cM was constructed with 6315 SNP/InDel markers developed using genotype-by-sequencing technology. A total of 16 genomic regions on eight sunflower chromosomes, 1, 2, 10, 12, 13, 14, 16 and 17 were associated with HR resistance, each explaining between 3.97 to 16.67% of the phenotypic variance for HR resistance. Eleven of these QTL had resistance alleles from the HR21 parent. Molecular markers flanking the QTL will facilitate marker-assisted selection breeding for HR resistance in sunflower.

On-field phenotypic evaluation of sunflower populations for broad-spectrum resistance to Verticillium leaf mottle and wilt

Sunflower Verticillium Wilt and Leaf Mottle (SVW), caused by Verticillium dahliae (Kleb.; Vd), is a soil-borne disease affecting sunflower worldwide. A single dominant locus, known as V1, was formerly effective in controlling North-American Vd races, whereas races from Argentina, Europe and an emerging race from USA overcome its resistance. This emphasizes the need for identifying broad-spectrum genetic resistance (BSR) sources. Here we characterize two sunflower mapping populations (MPs) for SVW resistance: a biparental MP and the association MP from the National Institute of Agricultural Technology (INTA), under field growing conditions. Nine field-trials (FTs) were conducted in highly infested fields in the most SVW-affected region of Argentina. Several disease descriptors (DDs), including incidence and severity, were scored across four phenological stages. Generalized linear models were fitted according to the nature of each variable, adjusting mean phenotypes for inbred lines across and within FTs. Comparison of these responses allowed the identification of novel BSR sources. Furthermore, we present the first report of SVW resistance heritability, with estimates ranging from 35 to 45% for DDs related to disease incidence and severity, respectively. This study constitutes the largest SVW resistance characterization reported to date in sunflower, identifying valuable genetic resources for BSR-breeding to cope with a pathogen of increasing importance worldwide.

Genetic loci underlying quantitative resistance to necrotrophic pathogens Sclerotinia and Diaporthe (Phomopsis), and correlated resistance to both pathogens

We provide results rooted in quantitative genetics, which combined with knowledge of candidate gene function, helps us to better understand the resistance to two major necrotrophic pathogens of sunflower. Necrotrophic pathogens can avoid or even benefit from plant defenses used against biotrophic pathogens, and thus represent a distinct challenge to plant populations in natural and agricultural systems. Sclerotinia and Phomopsis/Diaporthe are detrimental pathogens for many dicotyledonous plants, including many economically important plants. With no well-established methods to prevent infection in susceptible plants, host-plant resistance is currently the most effective strategy. Despite knowledge of a moderate, positive correlation in resistance to the two diseases in sunflower, detailed analysis of the genetics, in the same populations, has not been conducted. We present results of genome-wide analysis of resistance to both pathogens in a diversity panel of 218 domesticated sunflower genotypes of worldwide origin. We identified 14 Sclerotinia head rot and 7 Phomopsis stem canker unique QTLs, plus 1 co-located QTL for both traits, and observed extensive patterns of linkage disequilibrium between sites for both traits. Most QTLs contained one credible candidate gene, and gene families were common for the two disease resistance traits. These results suggest there has been strong, simultaneous selection for resistance to these two diseases and that a generalized mechanism for defense against these necrotrophic pathogens exists.

Exploring sunflower responses to Sclerotinia head rot at early stages of infection using RNA-seq analysis

Sclerotinia head rot (SHR), caused by the necrotrophic fungus Sclerotinia sclerotiorum, is one of the most devastating sunflower crop diseases. Despite its worldwide occurrence, the genetic determinants of plant resistance are still largely unknown. Here, we investigated the Sclerotinia-sunflower pathosystem by analysing temporal changes in gene expression in one susceptible and two tolerant inbred lines (IL) inoculated with the pathogen under field conditions. Differential expression analysis showed little overlapping among ILs, suggesting genotype-specific control of cell defense responses possibly related to differences in disease resistance strategies. Functional enrichment assessments yielded a similar pattern. However, all three ILs altered the expression of genes involved in the cellular redox state and cell wall remodeling, in agreement with current knowledge about the initiation of plant immune responses. Remarkably, the over-representation of long non-coding RNAs (lncRNA) was another common feature among ILs. Our findings highlight the diversity of transcriptional responses to SHR within sunflower breeding lines and provide evidence of lncRNAs playing a significant role at early stages of defense.

Unveiling the genetic basis of Sclerotinia head rot resistance in sunflower

BACKGROUND

Sclerotinia sclerotiorum is a necrotrophic fungus that causes Sclerotinia head rot (SHR) in sunflower, with epidemics leading to severe yield losses. In this work, we present an association mapping (AM) approach to investigate the genetic basis of natural resistance to SHR in cultivated sunflower, the fourth most widely grown oilseed crop in the world.

RESULTS

Our association mapping population (AMP), which comprises 135 inbred breeding lines (ILs), was genotyped using 27 candidate genes, a panel of 9 Simple Sequence Repeat (SSR) markers previously associated with SHR resistance via bi-parental mapping, and a set of 384 SNPs located in genes with molecular functions related to stress responses. Moreover, given the complexity of the trait, we evaluated four disease descriptors (i.e, disease incidence, disease severity, area under the disease progress curve for disease incidence, and incubation period). As a result, this work constitutes the most exhaustive AM study of disease resistance in sunflower performed to date. Mixed linear models accounting for population structure and kinship relatedness were used for the statistical analysis of phenotype-genotype associations, allowing the identification of 13 markers associated with disease reduction. The number of favourable alleles was negatively correlated to disease incidence, disease severity and area under the disease progress curve for disease incidence, whereas it was positevily correlated to the incubation period.

CONCLUSIONS

Four of the markers identified here as associated with SHR resistance (HA1848, HaCOI_1, G33 and G34) validate previous research, while other four novel markers (SNP117, SNP136, SNP44, SNP128) were consistently associated with SHR resistance, emerging as promising candidates for marker-assisted breeding. From the germplasm point of view, the five ILs carrying the largest combination of resistance alleles provide a valuable resource for sunflower breeding programs worldwide.