Short tandem repeat (STR) variation is rarely explored as a contributor to adaptive evolution. An intriguing mechanism involving STRs suggests that STRs function as \"tuning knobs\" of adaptation whereby stepwise changes in STR allele length have stepwise effects on phenotypes. Previously, we tested the predictions of the \"tuning knob\" model at the gene expression level by conducting an RNA-Seq experiment on natural populations of common sunflower (Helianthus annuus L.) transecting a well-defined cline from Kansas to Oklahoma. We identified 479 STRs with significant allele length effects on gene expression (eSTRs). In this study, we expanded the range to populations further north and south of the focal populations and used a targeted approach to study the relationship between STR allele length and gene expression in five selected eSTRs. Seeds from 96 individuals from six natural populations of sunflower from Nebraska and Texas were grown in a common garden. The individuals were genotyped at the five eSTRs, and gene expression was quantified with qRT-PCR. Linear regression models identified that eSTR length in comp26672 was significantly correlated with gene expression. Further, the length of comp26672 eSTR was significantly correlated with latitude across the range from Nebraska to Texas. The eSTR locus comp26672 was located in the CHUP1 gene, a gene associated with chloroplast movement in response to light intensity, which suggests a potential adaptive role for the eSTR locus. Collectively, our results from this targeted study show a consistent relationship between allele length and gene expression in some eSTRs across a broad geographical range in sunflower and suggest that some eSTRs may contribute to adaptive traits in common sunflower.

Water deficit stress reduces crop yield in field crops, including sunflowers, at any growth stage. In response, most plants activate hormonal and gene expression patterns to mitigate damage. In this study, we evaluated changes in the physiological and gene transcription levels of two sunflower (Helianthus annuus L.) inbred lines -one sensitive (B59 line) and one water stress-tolerant (B71)-in response to water stress, by using mannitol to simulate water deficit conditions, which provides moderate stress in both sunflower lines. The analyses of the accumulation of various phytohormones under this stress revealed that Jasmonic acid (JA) significantly increased in the shoots of both lines. Similarly, Salicylic acid (SA) increased in the shoots of both lines, although it also accumulated in B71 roots. In addition, Abscisic acid (ABA) and Indole-3-acetic acid (IAA) showed a considerable increase in the B59 shoots. Regarding the JA and SA pathways, the WRKY70 transcription levels were higher in the shoots of both lines and the roots of B71. The B59 line showed overtranscription of a gene related to the ABA pathway (XERICO) and genes associated with IAA (ARF9 and ARF16 genes). The B71 line, on the other hand, simultaneously triggered the JA, SA and ABA hormonal pathways in response to this stress condition. The ABA and JA hormonal pathways activated different TFs, such as RD20, RD22, RD26, ANAC19 and ANAC29, through MYC2. Both the JA and SA hormonal pathways activated the WRKY70 transcription factor. Altogether, each line triggered the hormonal and transcriptional pathways in response to water stress, although at varying intensities. The results suggest that the hormonal pathways of JA, SA, IAA and ABA, along with their primary associated genes, are activated in response to water deficit at the early growth stage in sunflower seedlings, which mitigates damage.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s12298-024-01497-8.

During sunflower growth, cold waves often occur and impede plant growth. Therefore, it is crucial to study the underlying mechanism of cold resistance in sunflowers. In this study, physiological analysis revealed that as cold stress increased, the levels of ROS, malondialdehyde, ascorbic acid, and dehydroascorbic acid and the activities of antioxidant enzymes increased. Transcriptomics further identified 10,903 DEGs between any two treatments. Clustering analysis demonstrated that the expression of MYB44a, MYB44b, MYB12, bZIP2 and bZIP4 continuously upregulated under cold stress. Cold stress can induce ROS accumulation, which interacts with hormone signals to activate cold-responsive transcription factors regulating target genes involved in antioxidant defense, secondary metabolite biosynthesis, starch and sucrose metabolism enhancement for improved cold resistance in sunflowers. Additionally, the response of sunflowers to cold stress may be independent of the CBF pathway. These findings enhance our understanding of cold stress resistance in sunflowers and provide a foundation for genetic breeding.

CONCLUSIONS: This study provided a non-destructive detection method with Vis-NIR hyperspectral imaging combining with physio-biochemical parameters in Helianthus annuus in response to Orobanche cumana infection that took insights into the monitoring of sunflower weed. Sunflower broomrape (Orobanche cumana Wallr.) is an obligate weed that attaches to the host roots of sunflower (Helianthus annuus L.) leading to a significant reduction in yield worldwide. The emergence of O. cumana shoots after its underground life-cycle causes irreversible damage to the crop. In this study, a fast visual, non-invasive and precise method for monitoring changes in spectral characteristics using visible and near-infrared (Vis-NIR) hyperspectral imaging (HSI) was developed. By combining the bands sensitive to antioxidant enzymes (SOD, GR), non-antioxidant enzymes (GSH, GSH + GSSG), MDA, ROS (O2-, OH-), PAL, and PPO activities obtained from the host leaves, we sought to establish an accurate means of assessing these changes and conducted imaging acquisition using hyperspectral cameras from both infested and non-infested sunflower cultivars, followed by physio-biochemical parameters measurement as well as analyzed the expression of defense related genes. Extreme learning machine (ELM) and convolutional neural network (CNN) models using 3-band images were built to classify infected or non-infected plants in three sunflower cultivars, achieving accuracies of 95.83% and 95.83% for the discrimination of infestation as well as 97.92% and 95.83% of varieties, respectively, indicating the potential of multi-spectral imaging systems for early detection of O. cumana in weed management.

Sunflower (Helianthus annuus) can potentially be used for uranium (U) phytoremediation. However, the factors influencing the absorption of U and its subsequent distribution within plant tissues remain unclear, including the effect of silicon (Si) which is known to increase metal tolerance. Here, using hydroponics, the effect of Si on the distribution and speciation of U in sunflower was examined using synchrotron-based X-ray fluorescence and fluorescence-X-ray absorption near-edge spectroscopy. It was found that ∼88 % of U accumulates within the root regardless of treatments. Without the addition of Si, most of the U appeared to bind to epidermis within the roots, whereas in the leaves, U primarily accumulated in the veins. The addition of Si alleviated U phytotoxicity and decreased U concentration in sunflower by an average of 60 %. In the roots, Si enhanced U distribution in cell walls and impeded its entry into cells, likely due to increased callose deposition. In the leaves, Si induced the sequestration of U in trichomes. However, Si did not alter U speciation and U remained in the hexavalent form. These results provide information on U accumulation and distribution within sunflower, and suggest that Si could enhance plant growth under high U stress.

Virus-Induced Gene Silencing (VIGS) is a versatile tool in plant science, yet its application to non-model species like sunflower demands extensive optimization due to transformation challenges. In this study, we aimed to elucidate the factors that significantly affect the efficiency of Agrobacterium-VIGS in sunflowers. After testing a number of approaches, we concluded that the seed vacuum technique followed by 6 h of co-cultivation produced the most efficient VIGS results. Genotype-dependency analysis revealed varying infection percentages (62-91%) and silencing symptom spreading in different sunflower genotypes. Additionally, we explored the mobility of tobacco rattle virus (TRV) and phenotypic silencing manifestation (photo-bleaching) across different tissues and regions of VIGS-infected sunflower plants. We showed the presence of TRV is not necessarily limited to tissues with observable silencing events. Finally, time-lapse observation demonstrated a more active spreading of the photo-bleached spots in young tissues compared to mature ones. This study not only offers a robust VIGS protocol for sunflowers but also provides valuable insights into genotype-dependent responses and the dynamic nature of silencing events, shedding light on TRV mobility across different plant tissues.

Stress-associated proteins (SAPs) are known to play an important role in plant responses to abiotic stresses. This study systematically identified members of the sunflower SAP gene family using sunflower genome data. The genes of the sunflower SAP gene family were analyzed using bioinformatic methods, and gene expression was assessed through fluorescence quantification (qRT-PCR) under salt and drought stress. A comprehensive analysis was also performed on the number, structure, collinearity, and phylogeny of seven Compositae species and eight other plant SAP gene families. The sunflower genome was found to have 27 SAP genes, distributed across 14 chromosomes. The evolutionary analysis revealed that the SAP family genes could be divided into three subgroups. Notably, the annuus variety exhibited amplification of the SAP gene for Group 3. Among the Compositae species, C. morifolium demonstrated the highest number of collinearity gene pairs and the closest distance on the phylogenetic tree, suggesting relative conservation in the evolutionary process. An analysis of gene structure revealed that Group 1 exhibited the most complex gene structure, while the majority of HaSAP genes in Group 2 and Group 3 lacked introns. The promoter analysis revealed the presence of cis-acting elements related to ABA, indicating their involvement in stress responses. The expression analysis indicated the potential involvement of 10 genes (HaSAP1, HaSAP3, HaSAP8, HaSAP10, HaSAP15, HaSAP16, HaSAP21, HaSAP22, HaSAP23, and HaSAP26) in sunflower salt tolerance. The expression of these 10 genes were then examined under salt and drought stress using qRT-PCR, and the tissue-specific expression patterns of these 10 genes were also analyzed. HaSAP1, HaSAP21, and HaSAP23 exhibited consistent expression patterns under both salt and drought stress, indicating these genes play a role in both salt tolerance and drought resistance in sunflower. The findings of this study highlight the significant contribution of the SAP gene family to salt tolerance and drought resistance in sunflower.

The accumulation of polyethylene microplastics (PE-MPs) in soil has raised considerable concerns; however, the effects of their persistence and mitigation on agroecosystems have not been explored. This study aimed to assess the detrimental effects of PE-MPs on a soil-plant system and evaluate their mitigation using a novel microbial consortium (MC). We incorporated low-density polyethylene (LDPE) and high-density polyethylene (HDPE) at two different concentrations, along with a control (0 %, 1 %, and 2 % w/w) into the sandy loam soil for a duration of 135 days. The samples were also treated with a novel MC and incubated for 135 days. The MC comprised three bacterial strains (Ralstonia pickettii (MW290933) strain SHAn2, Pseudomonas putida strain ShA, and Lysinibacillus xylanilyticus XDB9 (T) strain S7-10F), and a fungal strain (Aspergillus niger strain F1-16S). Sunflowers were subsequently cultivated, and physiological growth parameters were measured. The results showed that adding 2 % LDPE significantly decreased soil pH by 1.06 units compared to the control. Moreover, adding 2 % HDPE resulted in a more significant decrease in soil electrical conductivity (EC) relative to LDPE and the control. A dose-dependent increase in dissolved organic carbon (DOC) was observed, with the highest DOC found in 2 % LDPE. The addition of higher dosages of LDPE reduced soil bulk density (BD) more than HDPE. The addition of 2 % HDPE increased the water drop penetration time (WDPT) but decreased the mean weight diameter of soil aggregates (MWD) and water-stable aggregates (WSA) compared to LDPE. The results also revealed that higher levels of LDPE enhanced soil basal respiration (BR) and microbial carbon biomass (MBC). The interaction of MC and higher MP percentages considerably reduced soil pH, EC, BD, and WDPT but significantly increased soil DOC, MWD, WSA, BR, and MBC. Regarding plant growth, incorporating 2 % PE-MPs significantly reduced physiological responses of sunflower: chlorophyll content (Chl; -15.2 %), Fv/Fm ratio (-25.3 %), shoot dry weight (ShD; -31.3 %), root dry weight (RD; -40 %), leaf area (LA; -38.4 %), and stem diameter (StemD; -25 %) compared to the control; however, the addition of novel MC considerably reduced and ameliorated the harmful effects of 2 % PE-MPs on the investigated plant growth responses.

Leaf senescence is a complex trait which becomes crucial for grain filling because photoassimilates are translocated to the seeds. Therefore, a correct sync between leaf senescence and phenological stages is necessary to obtain increasing yields. In this study, we evaluated the performance of five deep machine-learning methods for the evaluation of the phenological stages of sunflowers using images taken with cell phones in the field. From the analysis, we found that the method based on the pre-trained network resnet50 outperformed the other methods, both in terms of accuracy and velocity. Finally, the model generated, Sunpheno, was used to evaluate the phenological stages of two contrasting lines, B481_6 and R453, during senescence. We observed clear differences in phenological stages, confirming the results obtained in previous studies. A database with 5000 images was generated and was classified by an expert. This is important to end the subjectivity involved in decision making regarding the progression of this trait in the field and could be correlated with performance and senescence parameters that are highly associated with yield increase.

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.