Phenotyping Sunflower Genetic Resources for Sclerotinia Head Rot Response: Assessing Variability for Disease Resistance Breeding

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.

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.

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.

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections

Sunflower germplasm collections are valuable resources for broadening the genetic base of commercial hybrids and ameliorate the risk of climate events. Nowadays, the most studied worldwide sunflower pre-breeding collections belong to INTA (Argentina), INRA (France), and USDA-UBC (United States of America-Canada). In this work, we assess the amount and distribution of genetic diversity (GD) available within and between these collections to estimate the distribution pattern of global diversity. A mixed genotyping strategy was implemented, by combining proprietary genotyping-by-sequencing data with public whole-genome-sequencing data, to generate an integrative 11,834-common single nucleotide polymorphism matrix including the three breeding collections. In general, the GD estimates obtained were moderate. An analysis of molecular variance provided evidence of population structure between breeding collections. However, the optimal number of subpopulations, studied via discriminant analysis of principal components (K = 12), the bayesian STRUCTURE algorithm (K = 6) and distance-based methods (K = 9) remains unclear, since no single unifying characteristic is apparent for any of the inferred groups. Different overall patterns of linkage disequilibrium (LD) were observed across chromosomes, with Chr10, Chr17, Chr5, and Chr2 showing the highest LD. This work represents the largest and most comprehensive inter-breeding collection analysis of genomic diversity for cultivated sunflower conducted to date.