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Key message: The HaOr5 resistance gene is located in a large genomic insertion containing putative resistance genes and provides resistance to O. cumana, preventing successful connection to the sunflower root vascular system. Orobanche cumana (sunflower broomrape) is a parasitic plant that is part of the Orobanchaceae family and specifically infests sunflower crops. This weed is an obligate parasitic plant that does not carry out photosynthetic activity or develop roots and is fully dependent on its host for its development. It produces thousands of dust-like seeds per plant. It possesses a high spreading ability and has been shown to quickly overcome resistance genes successively introduced by selection in cultivated sunflower varieties. The first part of its life cycle occurs underground. The connection to the sunflower vascular system is essential for parasitic plant survival and development. The HaOr5 gene provides resistance to sunflower broomrape race E by preventing the connection of O. cumana to the root vascular system. We mapped a single position of the HaOr5 gene by quantitative trait locus mapping using two segregating populations. The same location of the HaOr5 gene was identified by genome-wide association. Using a large population of thousands of F2 plants, we restricted the location of the HaOr5 gene to a genomic region of 193 kb. By sequencing the whole genome of the resistant line harboring the major resistance gene HaOr5, we identified a large insertion of a complex genomic region containing a cluster of putative resistance genes. [ABSTRACT FROM AUTHOR]

This article examines the relationship between sunflower plants and the parasitic plant broomrape. The study reveals that broomrape infiltrates sunflower roots by entering the host cells, creating a new compartment. The researchers also observed cell divisions in the sunflower roots near the attachment sites, potentially leading to root enlargement. The study suggests that the parasitic plant damages the host cell walls with enzymes, but the host plants only exhibit minimal defense responses. These findings contribute to our understanding of parasitic plant interactions and may aid in the development of resistance strategies. [Extracted from the article]

Introduction: Sunflower breeding for resistance to the parasitic plant sunflower broomrape (Orobanche cumana Wallr.) requires the identification of novel resistance genes. In this research, we conducted a genome-wide association study (GWAS) to identify QTLs associated with broomrape resistance. Methods: The marker-trait associations were examined across a germplasm set composed of 104 sunflower accessions. They were genotyped with a 600k AXIOM® genome-wide array and evaluated for resistance to three populations of the parasite with varying levels of virulence (races EFR, FGV, and GTK) in two environments. Results and Discussion: The analysis of the genetic structure of the germplasm set revealed the presence of two main groups. The application of optimized treatments based on the general linear model (GLM) and the mixed linear model (MLM) allowed the detection of 14 SNP markers significantly associated with broomrape resistance. The highest number of marker-trait associations were identified on chromosome 3, clustered in two different genomic regions of this chromosome. Other associations were identified on chromosomes 5, 10, 13, and 16. Candidate genes for the main genomic regions associated with broomrape resistance were studied and discussed. Particularly, two significant SNPs on chromosome 3 associated with races EFR and FGV were found at two tightly linked SWEET sugar transporter genes. The results of this study have confirmed the role of some QTL on resistance to sunflower broomrape and have revealed new ones that may play an important role in the development of durable resistance to this parasitic weed in sunflower. [ABSTRACT FROM AUTHOR]

Orobanche cumana Wall., sunflower broomrape, is one of the major pests for the sunflower crop. Breeding for resistant varieties in sunflower has been the most efficient method to control this parasitic weed. However, more virulent broomrape populations continuously emerge by overcoming genetic resistance. It is thus essential to identify new broomrape resistances acting at various stages of the interaction and combine them to improve resistance durability. In this study, 71 wild sunflowers and wild relatives accessions from 16 Helianthus species were screened in pots for their resistance to broomrape at the late emergence stage. From this initial screen, 18 accessions from 9 species showing resistance, were phenotyped at early stages of the interaction: the induction of broomrape seed germination by sunflower root exudates, the attachment to the host root and the development of tubercles in rhizotron assays. We showed that wild Helianthus accessions are an important source of resistance to the most virulent broomrape races, affecting various stages of the interaction: the inability to induce broomrape seed germination, the development of incompatible attachments or necrotic tubercles, and the arrest of emerged structure growth. Cytological studies of incompatible attachments showed that several cellular mechanisms were shared among resistant Helianthus species. [ABSTRACT FROM AUTHOR]

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Key message: This study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids. Abstract: Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids. [ABSTRACT FROM AUTHOR]

Understanding the genetic basis of phenotypic plasticity is crucial for predicting and managing climate change effects on wild plants and crops. Here, we combined crop modelling and quantitative genetics to study the genetic control of oil yield plasticity for multiple abiotic stresses in sunflower. First, we developed stress indicators to characterize 14 environments for three abiotic stresses (cold, drought and nitrogen) using the SUNFLO crop model and phenotypic variations of three commercial varieties. The computed plant stress indicators better explain yield variation than descriptors at the climatic or crop levels. In those environments, we observed oil yield of 317 sunflower hybrids and regressed it with three selected stress indicators. The slopes of cold stress norm reaction were used as plasticity phenotypes in the following genome-wide association study. Among the 65 534 tested Single Nucleotide Polymorphisms (SNPs), we identified nine quantitative trait loci controlling oil yield plasticity to cold stress. Associated single nucleotide polymorphisms are localized in genes previously shown to be involved in cold stress responses: oligopeptide transporters, lipid transfer protein, cystatin, alternative oxidase or root development. This novel approach opens new perspectives to identify genomic regions involved in genotype-by-environment interaction of a complex traits to multiple stresses in realistic natural or agronomical conditions. [ABSTRACT FROM AUTHOR]

Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA) of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS) can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore, GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET) over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%). Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but increased GCA-based prediction ability by 6.4%. Our results show that GS is a major improvement to breeding efficiency compared to the classical GCA modeling when either one or both parents are not well-characterized. This finding could therefore accelerate breeding through reducing phenotyping efforts and more effectively targeting for the most promising crosses. [ABSTRACT FROM AUTHOR]

Key message: SNP genotyping of 114 cultivated sunflower populations showed that the multiplication process and the main traits selected during breeding of sunflower cultivars drove molecular diversity of the populations. Abstract: The molecular diversity in a set of 114 cultivated sunflower populations was studied by single-nucleotide polymorphism genotyping. These populations were chosen as representative of the 400 entries in the INRA collection received or developed between 1962 and 2011 and made up of land races, open-pollinated varieties, and breeding pools. Mean allele number varied from 1.07 to 1.90. Intra-population variability was slightly reduced according to the number of multiplications since entry but some entries were probably largely homozygous when received. A principal component analysis was used to study inter-population variability. The first 3 axes accounted for 17% of total intra-population variability. The first axis was significantly correlated with seed oil content, more closely than just the distinction between oil and confectionary types. The second axis was related to the presence or absence of restorer genes and the third axis to flowering date and possibly to adaptation to different climates. Our results provide arguments highlighting the effect of the maintenance process on the within population genetic variability as well as on the impact of breeding for major agronomic traits on the between population variability of the collection. Propositions are made to improve sunflower population maintenance procedures to keep maximum genetic variability for future breeding. [ABSTRACT FROM AUTHOR]

The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought. Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives, including numerous extremophile species. Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences and required single-molecule real-time sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade and a sunflower-specific whole-genome duplication around 29 million years ago. An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs. [ABSTRACT FROM AUTHOR]

Orobanche cumana (sunflower broomrape) is an obligatory and non-photosynthetic root parasitic plant that specifically infects the sunflower. It is located in Europe and in Asia, where it can cause yield losses of over 80%. More aggressive races have evolved, mainly around the Black Sea, and broomrape can rapidly spread to new areas. Breeding for resistance seems to be the most efficient and sustainable approach to control broomrape infestation. In our study, we used a population of 101 recombinant inbred lines (RILs), derived from a cross between the two lines HA89 and LR1 (a line derived from an interspecific cross with Helianthus debilis). Rhizotrons, pots and field experiments were used to characterize all RILs for their resistance to O. cumana race F parasitism at three post vascular connection life stages: (i) early attachment of the parasite to the sunflower roots, (ii) young tubercle and (iii) shoot emergence. In addition, RIL resistance to race G at young tubercle development stage was evaluated in pots. The entire population was genotyped, and QTLs were mapped. Different QTLs were identified for each race (F from Spain and G from Turkey) and for the three stages of broomrape development. The results indicate that there are several quantitative resistance mechanisms controlling the infection by O. cumana that can be used in sunflower breeding. [ABSTRACT FROM AUTHOR]

Downy mildew of sunflower is caused by Plasmopara halstedii ( Farlow) Berlese & de Toni. Plasmopara halstedii is an obligate biotrophic oomycete pathogen that attacks annual Helianthus species and cultivated sunflower, Helianthus annuus. Depending on the sunflower developmental stage at which infection occurs, the characteristic symptoms range from young seedling death, plant dwarfing, leaf bleaching and sporulation to the production of infertile flowers. Downy mildew attacks can have a great economic impact on sunflower crops, and several Pl resistance genes are present in cultivars to protect them against the disease. Nevertheless, some of these resistances have been overcome by the occurrence of novel isolates of the pathogen showing increased virulence. A better characterization of P. halstedii infection and dissemination mechanisms, and the identification of the molecular basis of the interaction with sunflower, is a prerequisite to efficiently fight this pathogen. This review summarizes what is currently known about P. halstedii, provides new insights into its infection cycle on resistant and susceptible sunflower lines using scanning electron and light microscopy imaging, and sheds light on the pathogenicity factors of P. halstedii obtained from recent molecular data. Taxonomy Kingdom Stramenopila; Phylum Oomycota; Class Oomycetes; Order Peronosporales; Family Peronosporaceae; Genus Plasmopara; Species Plasmopara halstedii. Disease symptoms Sunflower seedling damping off, dwarfing of the plant, bleaching of leaves, starting from veins, and visible white sporulation, initially on the lower side of cotyledons and leaves. Plasmopara halstedii infection may severely impact sunflower seed yield. Infection process In spring, germination of overwintered sexual oospores leads to sunflower root infection. Intercellular hyphae are responsible for systemic plant colonization and the induction of disease symptoms. Under humid and fresh conditions, dissemination structures are produced by the pathogen on all plant organs to release asexual zoosporangia. These zoosporangia play an important role in pathogen dissemination, as they release motile zoospores that are responsible for leaf infections on neighbouring plants. Disease control Disease control is obtained by both chemical seed treatment (mefenoxam) and the deployment of dominant major resistance genes, denoted Pl. However, the pathogen has developed fungicide resistance and has overcome some plant resistance genes. Research for more sustainable strategies based on the identification of the molecular basis of the interaction are in progress. Useful websites, , (soon available). [ABSTRACT FROM AUTHOR]

Plant or soil water status is required in many scientific fields to understand plant responses to drought. Because the transcriptomic response to abiotic conditions, such as water deficit, reflects plant water status, genomic tools could be used to develop a new type of molecular biomarker. Using the sunflower ( Helianthus annuus L.) as a model species to study the transcriptomic response to water deficit both in greenhouse and field conditions, we specifically identified three genes that showed an expression pattern highly correlated to plant water status as estimated by the pre-dawn leaf water potential, fraction of transpirable soil water, soil water content or fraction of total soil water in controlled conditions. We developed a generalized linear model to estimate these classical water status indicators from the expression levels of the three selected genes under controlled conditions. This estimation was independent of the four tested genotypes and the stage (pre- or post-flowering) of the plant. We further validated this gene expression biomarker under field conditions for four genotypes in three different trials, over a large range of water status, and we were able to correct their expression values for a large diurnal sampling period. [ABSTRACT FROM AUTHOR]