Multi-scale characterisation of cold response reveals immediate and long-term impacts on cell physiology up to seed composition in sunflower.

Early sowing can help summer crops escape drought and can mitigate the impacts of climate change on them. However, it exposes them to cold stress during initial developmental stages, which has both immediate and long-term effects on development and physiology. To understand how early night-chilling stress impacts plant development and yield, we studied the reference sunflower line XRQ under controlled, semi-controlled and field conditions. We performed high-throughput imaging of the whole plant parts and obtained physiological and transcriptomic data from leaves, hypocotyls and roots. We observed morphological reductions in early stages under field and controlled conditions, with a decrease in root development, an increase in reactive oxygen species content in leaves and changes in lipid composition in hypocotyls. A long-term increase in leaf chlorophyll suggests a stress memory mechanism that was supported by transcriptomic induction of histone coding genes. We highlighted DEGs related to cold acclimation such as chaperone, heat shock and late embryogenesis abundant proteins. We identified genes in hypocotyls involved in lipid, cutin, suberin and phenylalanine ammonia lyase biosynthesis and ROS scavenging. This comprehensive study describes new phenotyping methods and candidate genes to understand phenotypic plasticity better in response to chilling and study stress memory in sunflower.

A cluster of putative resistance genes is associated with a dominant resistance to sunflower broomrape.

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.

Genetic control of abiotic stress-related specialized metabolites in sunflower.

BACKGROUND: Abiotic stresses in plants include all the environmental conditions that significantly reduce yields, like drought and heat. One of the most significant effects they exert at the cellular level is the accumulation of reactive oxygen species, which cause extensive damage. Plants possess two mechanisms to counter these molecules, i.e. detoxifying enzymes and non-enzymatic antioxidants, which include many classes of specialized metabolites. Sunflower, the fourth global oilseed, is considered moderately drought resistant. Abiotic stress tolerance in this crop has been studied using many approaches, but the control of specialized metabolites in this context remains poorly understood. Here, we performed the first genome-wide association study using abiotic stress-related specialized metabolites as molecular phenotypes in sunflower. After analyzing leaf specialized metabolites of 450 hybrids using liquid chromatography-mass spectrometry, we selected a subset of these compounds based on their association with previously known abiotic stress-related quantitative trait loci. Eventually, we characterized these molecules and their associated genes. RESULTS: We putatively annotated 30 compounds which co-localized with abiotic stress-related quantitative trait loci and which were associated to seven most likely candidate genes. A large proportion of these compounds were potential antioxidants, which was in agreement with the role of specialized metabolites in abiotic stresses. The seven associated most likely candidate genes, instead, mainly belonged to cytochromes P450 and glycosyltransferases, two large superfamilies which catalyze greatly diverse reactions and create a wide variety of chemical modifications. This was consistent with the high plasticity of specialized metabolism in plants. CONCLUSIONS: This is the first characterization of the genetic control of abiotic stress-related specialized metabolites in sunflower. By providing hints concerning the importance of antioxidant molecules in this biological context, and by highlighting some of the potential molecular mechanisms underlying their biosynthesis, it could pave the way for novel applications in breeding. Although further analyses will be required to better understand this topic, studying how antioxidants contribute to the tolerance to abiotic stresses in sunflower appears as a promising area of research.

Sunflower Hybrids and Inbred Lines Adopt Different Physiological Strategies and Proteome Responses to Cope with Water Deficit.

Sunflower is a hybrid crop that is considered moderately drought-tolerant and adapted to new cropping systems required for the agro-ecological transition. Here, we studied the impact of hybridity status (hybrids vs. inbred lines) on the responses to drought at the molecular and eco-physiological level exploiting publicly available datasets. Eco-physiological traits and leaf proteomes were measured in eight inbred lines and their sixteen hybrids grown in the high-throughput phenotyping platform Phenotoul-Heliaphen. Hybrids and parental lines showed different growth strategies: hybrids grew faster in the absence of water constraint and arrested their growth more abruptly than inbred lines when subjected to water deficit. We identified 471 differentially accumulated proteins, of which 256 were regulated by drought. The amplitude of up- and downregulations was greater in hybrids than in inbred lines. Our results show that hybrids respond more strongly to water deficit at the molecular and eco-physiological levels. Because of presence/absence polymorphism, hybrids potentially contain more genes than their parental inbred lines. We propose that detrimental homozygous mutations and the lower number of genes in inbred lines lead to a constitutive defense mechanism that may explain the lower growth of inbred lines under well-watered conditions and their lower reactivity to water deficit.

Similar Transcriptomic Responses to Early and Late Drought Stresses Produce Divergent Phenotypes in Sunflower (Helianthus annuus L.).

Cultivated sunflower (Helianthus annuus L.) exhibits numerous phenotypic and transcriptomic responses to drought. However, the ways in which these responses vary with differences in drought timing and severity are insufficiently understood. We used phenotypic and transcriptomic data to evaluate the response of sunflower to drought scenarios of different timing and severity in a common garden experiment. Using a semi-automated outdoor high-throughput phenotyping platform, we grew six oilseed sunflower lines under control and drought conditions. Our results reveal that similar transcriptomic responses can have disparate phenotypic effects when triggered at different developmental time points. Leaf transcriptomic responses, however, share similarities despite timing and severity differences (e.g., 523 differentially expressed genes (DEGs) were shared across all treatments), though increased severity elicited greater differences in expression, particularly during vegetative growth. Across treatments, DEGs were highly enriched for genes related to photosynthesis and plastid maintenance. A co-expression analysis identified a single module (M8) enriched in all drought stress treatments. Genes related to drought, temperature, proline biosynthesis, and other stress responses were overrepresented in this module. In contrast to transcriptomic responses, phenotypic responses were largely divergent between early and late drought. Early-stressed sunflowers responded to drought with reduced overall growth, but became highly water-acquisitive during recovery irrigation, resulting in overcompensation (higher aboveground biomass and leaf area) and a greater overall shift in phenotypic correlations, whereas late-stressed sunflowers were smaller and more water use-efficient. Taken together, these results suggest that drought stress at an earlier growth stage elicits a change in development that enables greater uptake and transpiration of water during recovery, resulting in higher growth rates despite similar initial transcriptomic responses.

The genomics of linkage drag in inbred lines of sunflower.

Crop wild relatives represent valuable sources of alleles for crop improvement, including adaptation to climate change and emerging diseases. However, introgressions from wild relatives might have deleterious effects on desirable traits, including yield, due to linkage drag. Here, we analyzed the genomic and phenotypic impacts of wild introgressions in inbred lines of cultivated sunflower to estimate the impacts of linkage drag. First, we generated reference sequences for seven cultivated and one wild sunflower genotype, as well as improved assemblies for two additional cultivars. Next, relying on previously generated sequences from wild donor species, we identified introgressions in the cultivated reference sequences, as well as the sequence and structural variants they contain. We then used a ridge-regression best linear unbiased prediction (BLUP) model to test the effects of the introgressions on phenotypic traits in the cultivated sunflower association mapping population. We found that introgression has introduced substantial sequence and structural variation into the cultivated sunflower gene pool, including >3,000 new genes. While introgressions reduced genetic load at protein-coding sequences, they mostly had negative impacts on yield and quality traits. Introgressions found at high frequency in the cultivated gene pool had larger effects than low-frequency introgressions, suggesting that the former likely were targeted by artificial selection. Also, introgressions from more distantly related species were more likely to be maladaptive than those from the wild progenitor of cultivated sunflower. Thus, breeding efforts should focus, as far as possible, on closely related and fully compatible wild relatives.

Expression complementation of gene presence/absence polymorphisms in hybrids contributes importantly to heterosis in sunflower.

INTRODUCTION: Numerous crops have transitioned to hybrid seed production to increase yields and yield stability through heterosis. However, the molecular mechanisms underlying heterosis and its stability across environments are not yet fully understood. OBJECTIVES: This study aimed to (1) elucidate the genetic and molecular mechanisms underlying heterosis in sunflower, and (2) determine how heterosis is maintained under different environments. METHODS: Genome-wide association (GWA) analyses were employed to assess the effects of presence/absence variants (PAVs) and stop codons on 16 traits phenotyped in the sunflower association mapping population at three locations. To link the GWA results to transcriptomic variation, we sequenced the transcriptomes of two sunflower cultivars and their F1 hybrid (INEDI) under both control and drought conditions and analyzed patterns of gene expression and alternative splicing. RESULTS: Thousands of PAVs were found to affect phenotypic variation using a relaxed significance threshold, and at most such loci the "absence" allele reduced values of heterotic traits, but not those of non-heterotic traits. This pattern was strengthened for PAVs that showed expression complementation in INEDI. Stop codons were much rarer than PAVs and less likely to reduce heterotic trait values. Hybrid expression patterns were enriched for the GO category, sensitivity to stimulus, but all genotypes responded to drought similarily - by up-regulating water stress response pathways and down-regulating metabolic pathways. Changes in alternative splicing were strongly negatively correlated with expression variation, implying that alternative splicing in this system largely acts to reinforce expression responses. CONCLUSION: Our results imply that complementation of expression of PAVs in hybrids is a major contributor to heterosis in sunflower, consistent with the dominance model of heterosis. This mechanism can account for yield stability across different environments. Moreover, given the much larger numbers of PAVs in plant vs. animal genomes, it also offers an explanation for the stronger heterotic responses seen in the former.

Gene regulatory network inference methodology for genomic and transcriptomic data acquired in genetically related heterozygote individuals.

MOTIVATION: Inferring gene regulatory networks in non-independent genetically related panels is a methodological challenge. This hampers evolutionary and biological studies using heterozygote individuals such as in wild sunflower populations or cultivated hybrids. RESULTS: First, we simulated 100 datasets of gene expressions and polymorphisms, displaying the same gene expression distributions, heterozygosities and heritabilities as in our dataset including 173 genes and 353 genotypes measured in sunflower hybrids. Secondly, we performed a meta-analysis based on six inference methods [least absolute shrinkage and selection operator (Lasso), Random Forests, Bayesian Networks, Markov Random Fields, Ordinary Least Square and fast inference of networks from directed regulation (Findr)] and selected the minimal density networks for better accuracy with 64 edges connecting 79 genes and 0.35 area under precision and recall (AUPR) score on average. We identified that triangles and mutual edges are prone to errors in the inferred networks. Applied on classical datasets without heterozygotes, our strategy produced a 0.65 AUPR score for one dataset of the DREAM5 Systems Genetics Challenge. Finally, we applied our method to an experimental dataset from sunflower hybrids. We successfully inferred a network composed of 105 genes connected by 106 putative regulations with a major connected component. AVAILABILITY AND IMPLEMENTATION: Our inference methodology dedicated to genomic and transcriptomic data is available at https://forgemia.inra.fr/sunrise/inference_methods. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Optimized cultivar deployment improves the efficiency and stability of sunflower crop production at national scale.

KEY MESSAGE: Crop simulation helps to analyze environmental impacts on crops and provides year-independent context information. This information is of major importance when deciding which cultivar to choose at sowing time. Plant breeding programs design new crop cultivars which, while developed for distinct populations of environments, are nevertheless grown over large areas during their time in the market. Over its cultivation area, the crop is exposed to highly diverse stress patterns caused by climatic uncertainty and multiple management options, which often leads to decreased expected crop performance. In this study, we aim to assess how finer spatial management of genetic resources could reduce the yield variance explained by genotype × environment interactions in a set of cropping environments and ultimately improve the efficiency and stability of crop production. We used modeling and simulation to predict the crop performance resulting from the interaction between cultivar growth and development, climate and soil conditions, and management practices. We designed a computational experiment that evaluated the performance of a collection of commercial sunflower cultivars in a realistic population of cropping conditions in France, built from extensive agricultural surveys. Distinct farming locations sharing similar simulated abiotic stress patterns were clustered together to specify environment types. We then used optimization methods to search for cultivars × environments combinations leading to increased yield expectations. Results showed that a single cultivar choice adapted to the most frequent environment-type in the population is a robust strategy. However, the relevance of cultivar recommendations to specific locations was gradually increasing with the knowledge of pedo-climatic conditions. We argue that this approach while being operational on current genetic material could act synergistically with plant breeding as more diverse material could enable access to cultivars with distinctive traits, more adapted to specific conditions.

Genome-wide and comparative phylogenetic analysis of senescence-associated NAC transcription factors in sunflower (Helianthus annuus).

BACKGROUND: Leaf senescence delay impacts positively in grain yield by maintaining the photosynthetic area during the reproductive stage and during grain filling. Therefore a comprehensive understanding of the gene families associated with leaf senescence is essential. NAC transcription factors (TF) form a large plant-specific gene family involved in regulating development, senescence, and responses to biotic and abiotic stresses. The main goal of this work was to identify sunflower NAC TF (HaNAC) and their association with senescence, studying their orthologous to understand possible functional relationships between genes of different species. RESULTS: To clarify the orthologous relationships, we used an in-depth comparative study of four divergent taxa, in dicots and monocots, with completely sequenced genomes (Arabidopsis thaliana, Vitis vinifera, Musa acuminata and Oryza sativa). These orthologous groups provide a curated resource for large scale protein sequence annotation of NAC TF. From the 151 HaNAC genes detected in the latest version of the sunflower genome, 50 genes were associated with senescence traits. These genes showed significant differential expression in two contrasting lines according to an RNAseq assay. An assessment of overexpressing the Arabidopsis line for HaNAC001 (a gene of the same orthologous group of Arabidopsis thaliana ORE1) revealed that this line displayed a significantly higher number of senescent leaves and a pronounced change in development rate. CONCLUSIONS: This finding suggests HaNAC001 as an interesting candidate to explore the molecular regulation of senescence in sunflower.

A multiscale approach reveals regulatory players of water stress responses in seeds during germination.

Seed germination is regulated by environmental factors, particularly water availability. Water deficits at the time of sowing impair the establishment of crop plants. Transcriptome and proteome profiling was used to document the responses of sunflower (Helianthus annuus) seeds to moderate water stress during germination in two hybrids that are nominally classed as drought sensitive and drought tolerant. Differences in the water stress-dependent accumulation reactive oxygen species and antioxidant enzymes activities were observed between the hybrids. A pathway-based analysis of the hybrid transcriptomes demonstrated that the water stress-dependent responses of seed metabolism were similar to those of the plant, with a decreased abundance of transcripts encoding proteins associated with metabolism and cell expansion. Moreover, germination under water stress conditions was associated with increased levels of transcripts encoding heat shock proteins. Exposure of germinating seeds to water stress specifically affected the abundance of a small number of proteins, including heat shock proteins. Taken together, these data not only identify factors that are likely to play a key role in drought tolerance during seed germination, but they also demonstrate the importance of the female parent in the transmission of water stress tolerance.

Exploring gene networks in two sunflower lines with contrasting leaf senescence phenotype using a system biology approach.

BACKGROUND: Leaf senescence is a complex process, controlled by multiple genetic and environmental variables. In sunflower, leaf senescence is triggered abruptly following anthesis thereby limiting the capacity of plants to keep their green leaf area during grain filling, which subsequently has a strong impact on crop yield. Recently, we performed a selection of contrasting sunflower inbred lines for the progress of leaf senescence through a physiological, cytological and molecular approach. Here we present a large scale transcriptomic analysis using RNA-seq and its integration with metabolic profiles for two contrasting sunflower inbred lines, R453 and B481-6 (early and delayed senescence respectively), with the aim of identifying metabolic pathways associated to leaf senescence. RESULTS: Gene expression profiles revealed a higher number of differentially expressed genes, as well as, higher expression levels in R453, providing evidence for early activation of the senescence program in this line. Metabolic pathways associated with sugars and nutrient recycling were differentially regulated between the lines. Additionally, we identified transcription factors acting as hubs in the co-expression networks; some previously reported as senescence-associated genes in model species but many are novel candidate genes. CONCLUSIONS: Understanding the onset and the progress of the senescence process in crops and the identification of these new candidate genes will likely prove highly useful for different management strategies to mitigate the impact of senescence on crop yield. Functional characterization of candidate genes will help to develop molecular tools for biotechnological applications in breeding crop yield.

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers.

INTRODUCTION: Plant and crop metabolomic analyses may be used to study metabolism across genetic and environmental diversity. Complementary analytical strategies are useful for investigating metabolic changes and searching for biomarkers of response or performance. METHODS AND OBJECTIVES: The experimental material consisted in eight sunflower lines with two line status, four restorers (R, used as males) and four maintainers (B, corresponding to females) routinely used for sunflower hybrid varietal production, respectively to complement or maintain the cytoplasmic male sterility PET1. These lines were either irrigated at full soil capacity (WW) or submitted to drought stress (DS). Our aim was to combine targeted and non-targeted metabolomics to characterize sunflower leaf composition in order to investigate the effect of line status genotypes and environmental conditions and to find the best and smallest set of biomarkers for line status and stress response using a custom-made process of variables selection. RESULTS: Five hundred and eighty-eight metabolic variables were measured by using complementary analytical methods such as 1H-NMR, MS-based profiles and targeted analyses of major metabolites. Based on statistical analyses, a limited number of markers were able to separate WW and DS samples in a more discriminant manner than previously published physiological data. Another metabolic marker set was able to discriminate line status. CONCLUSION: This study underlines the potential of metabolic markers for discriminating genotype groups and environmental conditions. Their potential use for prediction is discussed.

Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance.

Domesticated plants and animals often display dramatic responses to selection, but the origins of the genetic diversity underlying these responses remain poorly understood. Despite domestication and improvement bottlenecks, the cultivated sunflower remains highly variable genetically, possibly due to hybridization with wild relatives. To characterize genetic diversity in the sunflower and to quantify contributions from wild relatives, we sequenced 287 cultivated lines, 17 Native American landraces and 189 wild accessions representing 11 compatible wild species. Cultivar sequences failing to map to the sunflower reference were assembled de novo for each genotype to determine the gene repertoire, or 'pan-genome', of the cultivated sunflower. Assembled genes were then compared to the wild species to estimate origins. Results indicate that the cultivated sunflower pan-genome comprises 61,205 genes, of which 27% vary across genotypes. Approximately 10% of the cultivated sunflower pan-genome is derived through introgression from wild sunflower species, and 1.5% of genes originated solely through introgression. Gene ontology functional analyses further indicate that genes associated with biotic resistance are over-represented among introgressed regions, an observation consistent with breeding records. Analyses of allelic variation associated with downy mildew resistance provide an example in which such introgressions have contributed to resistance to a globally challenging disease.

Data describing the eco-physiological responses of twenty-four sunflower genotypes to water deficit.

This article presents experimental data describing the physiology and morphology of sunflower plants subjected to water deficit. Twenty-four sunflower genotypes were selected to represent genetic diversity within cultivated sunflower and included both inbred lines and their hybrids. Drought stress was applied to plants in pots at the vegetative stage using the high-throughput phenotyping platform Heliaphen at INRA Toulouse (France). Here, we provide data including specific leaf area, osmotic potential and adjustment, carbon isotope discrimination, leaf transpiration, plant architecture: plant height, leaf number, stem diameter. We also provide leaf areas of individual organs through time and growth rate during the stress period, environmental data such as temperatures, wind and radiation during the experiment. These data differentiate both treatment and the different genotypes and constitute a valuable resource to the community to study adaptation of crops to drought and the physiological basis of heterosis. It is available on the following repository: https://doi.org/10.25794/phenotype/er6lPW7V.

One Way to Achieve Germination: Common Molecular Mechanism Induced by Ethylene and After-Ripening in Sunflower Seeds.

Dormancy is an adaptive trait that blocks seed germination until the environmental conditions become favorable for subsequent vegetative plant growth. Seed dormancy is defined as the inability to germinate in favorable conditions. Dormancy is alleviated during after-ripening, a dry storage period, during which dormant (D) seeds unable to germinate become non-dormant (ND), able to germinate in a wide range of environmental conditions. The treatment of dormant seeds with ethylene (D/ET) promotes seed germination, and abscisic acid (ABA) treatment reduces non-dormant (ND/ABA) seed germination in sunflowers (Helianthus annuus). Metabolomic and transcriptomic studies have been performed during imbibition to compare germinating seeds (ND and D/ET) and low-germinating seeds (D and ND/ABA). A PCA analysis of the metabolites content showed that imbibition did not trigger a significant change during the first hours (3 and 15 h). The metabolic changes associated with germination capacity occurred at 24 h and were related to hexoses, as their content was higher in ND and D/ET and was reduced by ABA treatment. At the transcriptional level, a large number of genes were altered oppositely in germinating, compared to the low-germinating seeds. The metabolomic and transcriptomic results were integrated in the interpretation of the processes involved in germination. Our results show that ethylene treatment triggers molecular changes comparable to that of after-ripening treatment, concerning sugar metabolism and ABA signaling inhibition.

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.

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. 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.

Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling.

Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a modeling study using measured parameters as inputs for a crop simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used a crop simulation model to predict the impact on crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological model parameters to define ideotypes adapted to different environmental conditions.

Different genetic architectures underlie crop responses to the same pathogen: the {Helianthus annuus * Phoma macdonaldii} interaction case for black stem disease and premature ripening.

BACKGROUND: Phoma macdonaldii has been reported as the causal agent of black stem disease (BS) and premature ripening (PR) on sunflower. PR is considered as the most widespread and detrimental disease on sunflower in France. While genetic variability and QTL mapping for partial resistance of sunflower to stem, collar and roots attacks have been reported on plantlets in controlled conditions, this work aims to describe the genetic variability in a subset of a sunflower lines, and for the first time to map QTL involved in PR resistance evaluated in field conditions using controlled inoculation. RESULTS: An efficient and reliable method for inoculation used in field experiments induced stem base necrosis on up to 98% of all plants. A significant genetic variability for PR resistance in the field was detected among the 20 inbred lines of the core collection tested across the two years. For QTL mapping, the PR resistance evaluation was performed on two recombinant inbred lines (RIL) populations derived from the crosses XRQxPSC8 and FUxPAZ2 in two different years. QTL analyses were based on a newly developed consensus genetic map comprising 1007 non-redundant molecular markers. In each of the two RIL populations, different QTL involved in PR partial sunflower resistance were detected. The most significant QTL were detected 49 days post infection (DPI) on LG10 (LOD 7.7) and on LG7 (LOD 12.1) in the XRQxPSC8 and FUxPAZ2 RIL population, respectively. In addition, different QTL were detected on both populations for PR resistance measured between 14 and 35 DPI. In parallel, the incidence of natural attack of P. macdonaldii resulting in BS disease was recorded, showing that in these populations, the genetic of resistance to both diseases is not governed by the same factors. CONCLUSION: This work provides the first insights on the genetic architecture of sunflower PR resistance in the field. Moreover, the separate studies of symptoms on different organs and in time series allowed the identification of a succession of genetic components involved in the sunflower resistance to PR and BS diseases caused by Phoma macdonaldii along the development of the {plant * pathogen} interaction.