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.

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.