The sunflower (Helianthus annuus L.) is one of the most essential oil crops in the world. Several component traits, including flowering time, plant height, stem diameter, seed weight, and kernel weight, determine sunflower seed and oil yield. Although the genetic mechanisms governing the variation of these yield-related traits have been studied using various approaches, genome-wide association studies (GWAS) have not been widely applied to sunflowers. In this study, a set of 342 sunflower accessions was evaluated in 2019 and 2020 using an incomplete randomized block design, and GWAS was conducted utilizing two complementary approaches: the mixed linear model (MLM) and the fixed and random model circulating probability unification (farmCPU) model by fitting 226,779 high-quality SNPs. As a result, GWAS identified a number of trait-associated SNPs. Those SNPs were located close to several genes that may serve as a basis for further molecular characterization and provide promising targets for sunflower yield improvement.

Sunflower (Helianthus annuus L.) plays an essential role in meeting the demand for edible oil worldwide. The yield of sunflower seeds encompasses several component traits, including the disc diameter. Over three consecutive years, 2019, 2020, and 2022, we assessed phenotypic variation in disc diameter across a diverse set of sunflower accessions (N = 342) in replicated field trials. Upon aggregating the phenotypic data from multiple years, we estimated the broad sense heritability (H²) of the disc diameter trait to be 0.88. A subset of N = 274 accessions was genotyped by using the tunable genotyping‐by‐sequencing (tGBS) method, resulting in 226,779 high‐quality SNPs. Using these SNPs and the disc diameter phenotype, we conducted a genome‐wide association study (GWAS) employing two statistical approaches: the mixed linear model (MLM) and the fixed and random model circulating probability unification (farmCPU). The MLM and farmCPU GWAS approaches identified 106 and 8 significant SNPs located close to 53 and 21 genes, respectively. The MLM analysis identified two significant peaks: a prominent signal on chromosome 10 and a relatively weaker signal on chromosome 16, both of which were also detected by farmCPU. The genetic loci associated with disc diameter, as well as the related candidate genes, present promising avenues for further functional validation and serve as a basis for sunflower oil yield improvement.

Sunflower (Helianthus annuus L.) is exposed to a wide range of abiotic and biotic stresses, but the genes and regulatory features shared across these conditions are still not well defined. In this study, we carried out a transcriptome meta-analysis to identify conserved stress responsive genes in sunflower. Publicly available RNA-seq datasets covering seven major stress classes, including cold, drought, heat, salinity, flooding, Sclerotinia sclerotiorum infection, and Orobanche cumana parasitism, were integrated and analyzed using a common workflow. Across 11 transcriptomic contrasts, 11,348 meta differentially expressed genes were identified. Among them, 16 genes were shared across all contrasts and formed a conserved cross-stress response signature. Two of these genes were consistently upregulated, nine were consistently downregulated, and five showed variable expression across contrasts. Functional annotation linked these genes to phenylpropanoid metabolism, hormone related glycosylation, cell wall remodeling, water transport, and chloroplast associated processes, indicating that structural adjustment, metabolic regulation, and plastid related responses are recurring components of sunflower stress adaptation. Promoter analysis of stress responsive genes identified 864 motifs across 22 promoter sets. Annotation against the JASPAR2024 plant database showed that ERF/DREB, bHLH, NAC and WRKY were the most represented transcription factor families, with 223 transcription factors shared across all stress groups. Together, these results define a conserved set of stress responsive genes and associated regulatory features in sunflower and provide candidate genes and transcription factor families for future functional studies.