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.

The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution.

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.

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.

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.

Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modelling and genome-wide association.

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.

Molecular diversity of sunflower populations maintained as genetic resources is affected by multiplication processes and breeding for major traits.

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. 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.

Combined linkage and association mapping of flowering time in Sunflower (Helianthus annuus L.).

Association mapping and linkage mapping were used to identify quantitative trait loci (QTL) and/or causative mutations involved in the control of flowering time in cultivated sunflower Helianthus annuus. A panel of 384 inbred lines was phenotyped through testcrosses with two tester inbred lines across 15 location × year combinations. A recombinant inbred line (RIL) population comprising 273 lines was phenotyped both per se and through testcrosses with one or two testers in 16 location × year combinations. In the association mapping approach, kinship estimation using 5,923 single nucleotide polymorphisms was found to be the best covariate to correct for effects of panel structure. Linkage disequilibrium decay ranged from 0.08 to 0.26 cM for a threshold of 0.20, after correcting for structure effects, depending on the linkage group (LG) and the ancestry of inbred lines. A possible hitchhiking effect is hypothesized for LG10 and LG08. A total of 11 regions across 10 LGs were found to be associated with flowering time, and QTLs were mapped on 11 LGs in the RIL population. Whereas eight regions were demonstrated to be common between the two approaches, the linkage disequilibrium approach did not detect a documented QTL that was confirmed using the linkage mapping approach.

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.

Genetic analysis of phytosterol content in sunflower seeds.

Interest in phytosterol contents due to their potential benefits for human health has been largely documented in several crop species. Studies were focused mainly on total sterol content and their concentration or distribution in seed. This study aimed at providing new insight into the genetic control of total and individual sterol contents in sunflower seed through QTL analyses in a RIL population characterized over 2 years showing contrasted rainfall during seed filling. Results indicated that 13 regions on 9 linkage groups were involved in different phytosterol traits. Most of the QTL mapped were stable across years in spite of contrasted growing conditions. Some of them explained up to 30 % of phenotypic variation. Two QTL, located on LG10, near b1, and on LG14, were found to co-localize with QTL for oil content, indicating that likely, a part of the genetic variation for sterol content is only the result of genetic variation for oil content. However, three other QTL, stable over the 2 years, were found on LG1, LG4 and LG7 each associated with a particular class of sterols, suggesting that some enzymes known to be involved in the sterol metabolic pathway may determine the specificity of sterol profiles in sunflower seeds. These results suggest that it may be possible to introduce these traits as criteria in breeding programmes for quality in sunflower. The molecular markers linked to genetic factors controlling phytosterol contents could help selection during breeding programs.

Consensus mapping of major resistance genes and independent QTL for quantitative resistance to sunflower downy mildew.

Major gene resistance to sunflower downy mildew (Plasmopara halstedii) races 304 and 314 was found to segregate independently from the resistance to races 334, 307 and 304 determined by the gene Pl2, already positioned on Linkage Group (LG) 8 of sunflower molecular maps. Using a consensus SSR-SNP map constructed from the INEDI RIL population and a new RIL population FU × PAZ2, the positions of Pl2 and Pl5 were confirmed and the new gene, denoted Pl21, was mapped on LG13, at 8 cM from Pl5. The two RIL populations were observed for their quantitative resistance to downy mildew in the field and both indicated the existence of a QTL on LG8 at 20-40 cM from the major resistance gene cluster. In addition, for the INEDI population, a strong QTL on LG10, reported previously, was confirmed and a third QTL was mapped on LG7. A growth chamber test methodology, significantly correlated with field results, also revealed the major QTL on LG10, explaining 65 % of variability. This QTL mapped in the same area as a gene involved in stomatal opening and root growth, which may be suggested as a possible candidate to explain the control of this character. These results indicate that it should be possible to combine major genes and other resistance mechanisms, a strategy that could help to improve durability of sunflower resistance to downy mildew.

Association mapping for broomrape resistance in sunflower.

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.

An SSR-SNP Linkage Map of the Parasitic Weed Orobanche cumana Wallr. Including a Gene for Plant Pigmentation.

Sunflower broomrape (Orobanche cumana Wallr.) is a holoparasitic plant that causes major yield losses to sunflower crops in the Old World. Efforts to understand how this parasitic weed recognizes and interacts with sunflowers are important for developing long-term genetic resistance strategies. However, such studies are hampered by the lack of genetic tools for O. cumana. The objectives of this research were to construct a genetic linkage map of this species using SSR and SNP markers, and mapping the Pg locus that is involved in plant pigmentation. The genetic map was developed from the progenies of a cross between the O. cumana inbred lines EK-12 and EK-A1, which originated from populations belonging to two distant and geographically separated gene pools identified in Spain. The inbred lines also differed in plant pigmentation, with EK-A1 lacking anthocyanin pigmentation (pgpg genotype). A genetic map comprising 26 SSR and 701 SNP markers was constructed, which displayed 19 linkage groups (LGs), corresponding to the 19 chromosome pairs of O. cumana. The total length of the map was 1795.7 cM, with an average distance between two adjacent positions of 2.5 cM and a maximum map distance of 41.9 cM. The Pg locus mapped to LG19 between the SNP markers OS02468 and OS01653 at 7.5 and 3.4 cM, respectively. This study constitutes the first linkage map and trait mapping study in Orobanche spp., laying a key foundation for further genome characterization and providing a basis for mapping additional traits such as those having a key role in parasitism.

Genomic Prediction of Sunflower Hybrids Oil Content.

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.

Extraction of high-molecular-weight genomic DNA for long-read sequencing of single molecules.

De novo sequencing of complex genomes is one of the main challenges for researchers seeking high-quality reference sequences. Many de novo assemblies are based on short reads, producing fragmented genome sequences. Third-generation sequencing, with read lengths >10 kb, will improve the assembly of complex genomes, but these techniques require high-molecular-weight genomic DNA (gDNA), and gDNA extraction protocols used for obtaining smaller fragments for short-read sequencing are not suitable for this purpose. Methods of preparing gDNA for bacterial artificial chromosome (BAC) libraries could be adapted, but these approaches are time-consuming, and commercial kits for these methods are expensive. Here, we present a protocol for rapid, inexpensive extraction of high-molecular-weight gDNA from bacteria, plants, and animals. Our technique was validated using sunflower leaf samples, producing a mean read length of 12.6 kb and a maximum read length of 80 kb.

Effector Polymorphisms of the Sunflower Downy Mildew Pathogen Plasmopara halstedii and Their Use to Identify Pathotypes from Field Isolates.

The obligate biotroph oomycete Plasmopara halstedii causes downy mildew on sunflower crop, Helianthus annuus. The breakdown of several Pl resistance genes used in sunflower hybrids over the last 25 years came along with the appearance of new Pl. halstedii isolates showing modified virulence profiles. In oomycetes, two classes of effector proteins, key players of pathogen virulence, are translocated into the host: RXLR and CRN effectors. We identified 54 putative CRN or RXLR effector genes from transcriptomic data and analyzed their genetic diversity in seven Pl. halstedii pathotypes representative of the species variability. Pl. halstedii effector genes were on average more polymorphic at both the nucleic and protein levels than random non-effector genes, suggesting a potential adaptive dynamics of pathogen virulence over the last 25 years. Twenty-two KASP (Competitive Allele Specific PCR) markers designed on polymorphic effector genes were genotyped on 35 isolates belonging to 14 Pl. halstedii pathotypes. Polymorphism analysis based on eight KASP markers aims at proposing a determination key suitable to classify the eight multi-isolate pathotypes into six groups. This is the first report of a molecular marker set able to discriminate Pl. halstedii pathotypes based on the polymorphism of pathogenicity effectors. Compared to phenotypic tests handling living spores used until now to discriminate Pl. halstedii pathotypes, this set of molecular markers constitutes a first step in faster pathotype diagnosis of Pl. halstedii isolates. Hence, emerging sunflower downy mildew isolates could be more rapidly characterized and thus, assessment of plant resistance breakdown under field conditions should be improved.

Sunflower Resistance to Broomrape (Orobanche cumana) Is Controlled by Specific QTLs for Different Parasitism Stages.

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.

Repetitive sequence-derived markers tag centromeres and telomeres and provide insights into chromosome evolution in Brassica napus.

Centromeres and telomeres are obvious markers on chromosomes but their location on genetic maps is difficult to determine, which hampers many basic and applied research programmes. In this study, we used the characteristic distribution of five Brassica repeated sequences to generate physically anchored molecular markers tentatively tagging Brassica centromeres (84 markers) and telomeres (31 markers). These markers were mapped to the existing oilseed rape genetic map. Clusters of centromere-related loci were observed on 14 linkage groups; in addition to previous reports, we could thus provide information about the most likely position of centromeres on 17 of the 19 B. napus linkage groups. The location of centromeres on linkage groups usually matches their position on chromosomes and coincides with sites of evolutionary breakage between chromosomes. Most telomere sequence-derived markers mapped interstitially or in the proximity of centromeres; this result echoes previous reports on many eukaryote genomes and may reflect different forms of chromosome evolution. Seven telomere sequence-derived markers were located at the outermost positions of seven linkage groups and therefore probably tagged telomeres.