The ASTR Team
The ASTR team aims to produce genetic knowledge to adapt sunflower cultivation to the challenges of agroecological transition.
Sunflower is the fourth most important oilseed crop globally and the second in France. Its low water and input requirements, along with its short growth cycle, give it a highly favorable ecological profile. It is a key component of future agricultural systems (Debaeke et al., 2021), and its production has increased by 44% over the past 10 years (source: USDA).
Primarily cultivated in environments prone to water stress, our research focuses on:
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The genetic control of yield plasticity in response to water stress and cold temperatures following early sowing to avoid drought
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The molecular mechanisms involved in responses to abiotic stresses in innovative cropping systems
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The impact of climate change on sunflower’s attractiveness to pollinators
Our Research Resources
We develop resources on three levels to support our work:
Phenotyping Tools with Phenotoul
The team created and continues to manage the high-throughput phenotyping platform Heliaphen. This platform is part of the local infrastructure Phenotoul (which includes Agrophen for field conditions and TPMP for controlled conditions), itself part of Phenome-Emphasis, a national research infrastructure integrated into the European network EPPN Emphasis. Find more information here.
We work closely with Hiphen to develop high-throughput phenotyping pipelines tailored to sunflower and aligned with our research themes.
Collaborations and partnerships: TPMP platform (LIPME), Agroecology and Crop Phenotyping Unit, LEPSE, MISTEA, Hiphen
Genetic Resources with the Sunflower Biological Resource Center (CRB Tournesol)
As part of public-private projects, we develop and characterize recombinant populations, NAM populations, diversity panels, and introgression line populations. We utilize the natural genetic diversity in the CRB Tournesol, including both cultivated and wild varieties, to perform crosses that will contribute to the development of tomorrow’s sunflower cultivars. Explore the CRB Tournesol here.
Collaborations and partnerships: CRB Tournesol and SPI team (LIPME), Lidea, Limagrain, MAS Seeds, RAGT, Syngenta, Corteva
Genomic Resources with the ICSG
The team is actively involved in the International Consortium for Sunflower Genomics (ICSG), alongside the SPI team and the bioinformatics platform at LIPME, to sequence the genetic diversity of the Helianthus genus and cultivated sunflower lines. We collaborate internationally with the University of British Columbia in Vancouver and the University of Georgia in Athens to pool our expertise and generate genomic references for the Helianthus genus, supporting both academic research and varietal innovation. Access the Heliagene genomics portal here.
Collaborations and partnerships: Bioinformatics platform and SPI team (LIPME), MAS Seeds, Lidea, RAGT, Limagrain, Syngenta, Corteva
OUR PROJECTS
Coordination: Adam Vandergen, INRAE Dijon
Funding: EU Research and Innovation Action, HORIZON — €6M
Partners: INRAE Dijon (FR), INRAE Transfert Paris (FR), Helmholtz-Zentrum für Umweltforschung Leipzig (DE), University of Reading (UK), Wageningen University (NL), Stichting Wageningen Research (NL), Lund University (SE), CSIC Madrid (ES), Albert-Ludwigs-Universität Freiburg (DE), Pensoft Publishers (BG), CzechGlobe Brno (CZ), University of Mons (BE), University of Ljubljana (SI), University of Padova (IT), WCMC LBG Cambridge (UK), Associació Paisatges Vius (ES), Maisadour Semences Romania SRL (RO), CIA Padova (IT).
Associated partners: WBF Agroscope Bern (CH), Agridea Fribourg (CH), IARCAAS Beijing (CN), China West Normal University Nanchong (CN), Gansu Agricultural University Lanzhou (CN).
Duration: 2025–2028
COPER — Cold Oil Yield Plasticity in Sunflower
In the face of climate change, early sowing has emerged as an effective strategy to help crops escape water stress. However, the early developmental stages of sunflower are then exposed to lower temperatures than under traditional sowing conditions. To address this, phenotypic, genetic, and transcriptomic characterization work began in 2021 within the COPER project.
Coordination: Nicolas Langlade
Funding: INRAE–Syngenta bilateral collaboration agreement
Associated PhD: Jean Leconte, University of Toulouse — Genetic, transcriptomic, and physiological characterization of a QTL controlling yield tolerance to cold in sunflower. Supervised by Nicolas Langlade
Duration: 2019–2025
CIMS-ON
The CIMS-ON project (Phenotyping of cover crop varieties in long intercrops for complementary services to sunflower), led by UMR AGIR, aims to phenotype several cover crop species that may provide services to sunflower, such as nutrient management (uptake and restitution) and control of pests (Verticillium and Orobanche). The ASTR team will take advantage of the project’s experimental setup to study the interactions between these cover crops, senescence, nitrogen and water availability at the end of the cycle, and the genetic bases that may play a role under these conditions.
Funding: Institut Carnot Plant2Pro
Coordination: Lionel Alletto (UMR AGIR)
Associated PhD: Lucie Souques, University of Toulouse — Study of the abiotic effects of multi-service cover crop species and varieties with different growth cycles on various sunflower varieties. Co-supervision: Lionel Alletto and Nicolas Langlade
IPHARD
The IPHARD project (Ideotyping and Phenotyping for the Adaptation of Soybean and Sunflower Varieties to Relay or Catch Cropping Systems) aims to identify the phenotypic traits of soybean and sunflower of economic interest for relay and catch cropping systems.
The ASTR team contributes to the project on the sunflower catch-crop component, focusing on characterizing abiotic stresses experienced by sunflower under these conditions. Using our expertise in phenotyping sunflower responses to water stress on the Heliaphen platform, we characterize cultivated varieties to identify which phenotypic traits confer better drought tolerance traits that can then be targeted in breeding programs adapted to this cropping system.
Funding: French Ministry of Agriculture (CASDAR)
Coordination: Gilles Tison and Philippe Debaeke
Duration: 2021–2024
Heliopollen
The Heliopollen project (Impact of water stress on sunflower attractiveness to pollinating insects) investigates how water stress affects various traits involved in attractiveness: floret morphology, pollen quantity and composition, nectar volume and sugar composition, and the expression of genes involved in nectar production.
A fundamental part of the study focuses on three sunflower lines selected for their differential tolerance to water stress. A more applied component measures these traits across a panel of hybrids to assess the effect of genetic progress on phenotypic traits related to attractiveness, in connection with the Promosol Demeler project.
Coordination: Olivier Catrice and Nicolas Langlade
Funding: Promosol
Duration: 2021–2023
EU RIA HELEX
HelEx is a four-year research and innovation project supported by the European Union’s Horizon Europe program.
The €5.5 million project aims to identify molecular and genetic strategies to adapt sunflower cultivation to climate change while improving its environmental footprint.
The main objective is to create new sunflower varieties that are more resistant to drought and extreme climatic conditions, using Helianthus extremophilus varieties.
HelEx : Improving sunflower resilience in the face of climate challenges
Abiotic stresses, particularly drought and heat, have a significant impact on plant physiology and development, and consequently on crop yields.
In Europe, drought has a pronounced effect on agriculture, especially for sunflower producers. Wild plant species — in particular the 49 Helianthus species native to North America — have evolved to withstand such stresses.
These species have developed resilience strategies that allow them to thrive in extreme environments, such as deserts and high-altitude areas. They remain highly attractive to pollinators, which is crucial since they are self-incompatible. The attractiveness of sunflower to pollinators depends on visual and olfactory cues, as well as rewards like nectar and pollen, all of which may be affected by environmental conditions.
Improving sunflowers resilence trough wild genetics and advanced technologies
HelEx aims to harness the genetic and molecular mechanisms developed by wild Helianthus species to adapt to extreme climates.
The goal is to integrate these mechanisms into cultivated sunflowers in order to maintain seed quality and pollinator resources. Several projects have focused on sunflower tolerance to drought and other abiotic stresses, mainly at the molecular level.
HelEx seeks to go beyond existing knowledge by developing innovative phenotyping methods using AI, producing multi-omics networks, and identifying new haplotypes from wild Helianthus species.
The project also aims to enhance sunflower breeding programs by addressing challenges such as the narrow genetic base of cultivated sunflower and the complex nature of the traits being targeted.
The 18 HelEx Partners
The HelEx partners bring together leading academic research institutes specialized in sunflower and world-leading seed companies from seven European countries France, Germany, the Netherlands, Serbia, Austria, Romania, and Poland, as well as from Canada and the United States.
AGRI4POL Promoting sustainable agriculture for pollinators
The threats facing pollinators and the pollination services that support agriculture and provide benefits to populations are a global issue. AGRI4POL’s ambition is to assist the transition of agriculture, shifting from a pressure on pollinators to a positive force for the management and restoration of pollinator biodiversity, crop pollination services, and co-benefits for ecosystems and communities. To achieve this transition toward agricultural systems and value chains that are more favorable to pollinators, AGRI4POL will advance scientific understanding of the relationships between cropping systems and pollinators, from the crop gene level to the agroecosystem.
By evaluating the genetic basis of floral traits in crops that attract and reward pollinators, we will identify candidate crop lines suitable for breeding future pollinator-friendly varieties. We will study how pollinator–crop interactions change across space and time, influenced by crop species and variety diversity and rotation, ecological infrastructure (EI) including landscape elements and non-cultivated habitats, as well as future climate and land-use changes. Synthesizing this information—from the genetic to the agroecosystem scale will enable us to provide integrated recommendations to optimize landscapes for crop pollination, pollinator biodiversity, and multiple ecosystem benefits.
The research of AGRI4POL will be guided and supported by early and sustained multi-stakeholder engagement throughout the agri-food chains, ensuring its relevance and the acceptability of management options by farmers and society. This multi-stakeholder approach will also assess the socio-economic and political barriers and opportunities affecting the feasibility and adoption of pollinator-friendly agriculture at [sub]national, European, and international levels. AGRI4POL will thus demonstrate to farmers, agri-food actors, policymakers, and society the importance of pollinator-friendly agriculture for food security and sustainability goals (European Green Deal, Nature Restoration Law, United Nations SDGs).
Our previous projects
PIA SUNRISE
The SUNRISE project : SUNflower Resources to Improve yield Stability in a changing Environment aims to develop knowledge, resources, and tools for sunflower to adapt this crop to the challenges of climate change, particularly by maintaining its productivity under drought conditions.
The project brings together multiple disciplines: genetics, genomics, physiology, agronomy, and social sciences. It involves research stakeholders (9 INRAE and university laboratories), the technical institute for oilseed crops, and 6 biotechnology and seed companies with the goal not to work for but with field actors, ensuring a faster and more effective transfer of the knowledge, methods, and resources generated.
The project has strong roots in the southwest of France, particularly in Toulouse, which has further strengthened the city’s visibility as the world capital of sunflower research and breeding.
SUNRISE was a central project of the ASTR team between 2012 and 2020 and continues today through the analysis of the data produced and the exploration of new research directions opened by this large-scale initiative.
SUNRISE IN NUMBERS
Budget
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Total: €21M
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Grant: €7M (INRAE €4.3M)
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Public self-funding: €7M (INRAE €4.7M)
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Private self-funding: €7M
Funding: French National Research Agency (ANR-11-BTBR-005)
Duration: September 2012 – December 2020 (8 years and 4 months)
Coordination: Patrick Vincourt (2012–2013) and Nicolas Langlade (2014–2020)
16 Partners
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9 public research laboratories:
INRAE LIPME, INRAE AGIR, INRAE MIAT, INRAE CNRGV, INRAE EPGV, Sorbonne University, INRAE GQE, Toulouse 1 University (LEREPS), INRAE BFP -
1 technical institute: Terres Inovia
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1 biotechnology company: Innolea
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5 seed companies: Caussade Semences (now Lidea), MAS Seeds, RAGT, Soltis, Syngenta
Personnel
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Public staff: 86 people, including 32 researchers, 3 PhD students, and 10 postdoctoral researchers
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Private sector: around 100 scientists
Data Produced
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~100 experiments, including:
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45 field trials in France, Romania, Chile, and Argentina
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~60 experiments on phenotyping platforms (Phenotoul)
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~6,700 sunflower genotypes created or used
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7,020 plants phenotyped on the Heliaphen platform
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Over 2,000 million SNP genotyping data points (chips and resequencing)
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~1 million agronomic data entries available in the SUNRISE database
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5 million transcript quantification measurements
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1.2 million DNA methylation level measurements
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850,000 metabolite quantification measurements
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172,000 protein quantification measurements
Key Results
1 – Sequencing of the first sunflower reference genome (Badouin et al., 2017, Nature)
Achieved through close collaboration between LIPME, CNRGV, and GeT to acquire a next-generation sequencer and overcome the bottleneck of assembling large, complex plant genomes. Two additional sunflower genomes were sequenced as part of SUNRISE.
The methodology developed became a genomics standard and has since been widely reused for sequencing dozens of plants, animals, and microorganisms (rose, Medicago, grapevine, broomrape, human, macaque, bee, etc.).
2 – Identification of the genetic control of drought tolerance (Mangin et al., 2017; Gosseau et al., 2019; and ongoing valorization)
A combined approach of quantitative genetics and agronomic modeling developed at LIPME and AGIR, together with private partners’ trials, made it possible to identify sunflower types adapted to various European climates and future climate scenarios.
Integration of these results with gene regulatory modeling at MIAT revealed gene networks involved in drought tolerance. These networks have already been targeted by modern breeding and remain a priority for future sunflower improvement.
3 – Development of high-throughput phenotyping tools (Gosseau et al., 2019)
SUNRISE enabled close collaboration between UEGCA, LIPME, and the PHENOME investment program, leading to the development of the first high-throughput phenotyping tools for sunflower.
These tools were applied during the largest sunflower trial ever conducted at INRAE in 2017: 1,800 plots over 3 hectares at the Langlade experimental domain, characterized using drones.
This work also led to the creation of the Phenotoul infrastructure, which uniquely brings together greenhouses, semi-controlled environments, and field trials (TPMP, Heliaphen, Agrophen) on a single site.
4 – Eco-innovations for the seed sector and integration into variety evaluation systems (Galliano et al., 2017)
SUNRISE helped conceptualize eco-innovation in plant breeding and explore the barriers to adoption by farmers in France and Europe. This was achieved through collaborative work between AGIR and LEREPS, with support from the seed companies’ international networks involved in the project.
5 – Development of genetic material incorporating wild genetic diversity
The genetic resources produced through SUNRISE are unique. The Sunflower Biological Resource Center (CRB Tournesol) at LIPME, in partnership with seed companies, developed:
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2,437 recombinant inbred lines
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448 introgression lines with wild sunflower backgrounds
SUNRISE enabled their molecular characterization: ~3,500 lines were genotyped at high density, laying the groundwork for future exploitation of this genetic diversity in upcoming projects.
Other previous projects
Heliasen: Analysis and Phenotyping of Leaf Senescence in Sunflowerz
Coordination : Philippe Burger et Nicolas Langlade
Finacement : Promosol
Année : 2017-2020
HeliaDiv 2: Evaluation and Management of Helianthus Network Lines through Genomic Selection
Coordination : Brigitte Mangin
Financement : Promosol
Année : 2017-2020
HeliaDiv: Genetic Resources of the Helianthus Genus – Molecular Polymorphism and Biodiversity Conservation
Coordination : Patrick Vincourt
Financement : Promosol
Année : 2013-2016
Oleosol
Coordination : Patrick Vincourt
Financement : FUI, Midi-Pyrénées region, European Fund for Regional Development
Année : 2010-2013
Sunyfuel
Coordination : Patrick Vincourt
Financement : ANR
Année : 2008-2011
MEMBERS
scientific output
Adiredjo, AL, Casadebaig, P., Langlade, N., Lamaze, T., Grieu, P., 2018. Genetic Analysis of the Transpiration Control in Sunflower (Helianthus Annuus L) Subjected to Drought. VEGETOS: An International Journal of Plant Research 2018. https://doi.org/10.4172/2229-4473.1000368
Adiredjo, AL, Navaud, O., Muños, S., Langlade, NB, Lamaze, T., Grieu, P., 2014. Genetic Control of Water Use Efficiency and Leaf Carbon Isotope Discrimination in Sunflower (Helianthus annuus L.) Subjected to Two Drought Scenarios. PLoS ONE 9, e101218.
Andrianasolo, FN, Casadebaig, P., Langlade, N., Debaeke, P., Maury, P., 2016. Effects of plant growth stage and leaf aging on the response of transpiration and photosynthesis to water deficit in sunflower. Functional Plant Biology 43, 797–805.
Badouin, H., Gouzy, J., Grassa, CJ, Murat, F., Staton, SE, Cottret, L., Lelandais-Brière, C., Owens, GL, Carrère, S., Mayjonade, B., Legrand , L., Gill, N., Kane, NC, Bowers, JE, Hubner, S., Bellec, A., Bérard, A., Bergès, H., Blanchet, N., Boniface, M.-C., Brunel, D., Catrice, O., Chaidir, N., Claudel, C., Donnadieu, C., Faraut, T., Fievet, G., Helmstetter, N., King, M., Knapp, SJ, Lai , Z., Le Paslier, M.-C., Lippi, Y., Lorenzon, L., Mandel, JR, Marage, G., Marchand, G., Marquand, E., Bret-Mestries, E., Morien , E., Nambeesan, S., Nguyen, T., Pegot-Espagnet, P., Pouilly, N., Raftis, F., Sallet, E., Schiex, T., Thomas, J., Vandecasteele, C. , Varès, D., Vear, F., Vautrin, S., Crespi, M., Mangin, B., Burke, JM, Salse, J., Muños, S., Vincourt, P., Rieseberg, LH, Langlade , NB, 2017. The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution. Nature 546, 148–152. https://doi.org/10.1038/nature22380
Balliau, T., Duruflé, H., Blanchet, N., Blein-Nicolas, M., Langlade, NB, Zivy, M., 2021. Proteomic data from leaves of twenty-four sunflower genotypes under water deficit. OCL 28, 12. https://doi.org/10.1051/ocl/2020074
Berton, T., Bernillon, S., Fernandez, O., Duruflé, H., Flandin, A., Cassan, C., Jacob, D., Langlade, NB, Gibon, Y., Moing, A., 2021 Leaf metabolomic data of eight sunflower lines and their sixteen hybrids under water deficit. OCL 28, 42. https://doi.org/10.1051/ocl/2021029
Blanchet, N., Casadebaig, P., Debaeke, P., Duruflé, H., Gody, L., Gosseau, F., Langlade, NB, Maury, P., 2018. Data describing the eco-physiological responses of twenty -four sunflower genotypes to water deficit. Data Brief 21, 1296–1301. https://doi.org/10.1016/j.dib.2018.10.045
Bonnafous, F., Fievet, G., Blanchet, N., Boniface, M.-C., Carrère, S., Gouzy, J., Legrand, L., Marage, G., Bret-Mestries, E., Munos, S., Pouilly, N., Vincourt, P., Langlade, N., Mangin, B., 2018. Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids. Theor. Appl. Broom. 131, 319–332. https://doi.org/10.1007/s00122-017-3003-4
Bordat, A., Marchand, G., Langlade, NB, Pouilly, N., Muños, S., Dechamp-Guillaume, G., Vincourt, P., Bret-Mestries, E., 2017. Different genetic architectures underlie crop responses to the same pathogen: the {Helianthus annuus * Phoma macdonaldii} interaction case for black stem disease and premature ripening. BMC Plant Biology 17, 167. https://doi.org/10.1186/s12870-017-1116-1
Debaeke, P., Casadebaig, P., Flenet, F., Langlade, N., 2017. Sunflower crop and climate change: vulnerability, adaptation, and mitigation potential from case-studies in Europe. OCL 24, D102. https://doi.org/10.1051/ocl/2016052
Debaeke, P., Casadebaig, P., Langlade, NB, 2021. New challenges for sunflower ideotyping in changing environments and more ecological cropping systems. OCL 28, 29. https://doi.org/10.1051/ocl/2021016
Fernandez, O., Urrutia, M., Bernillon, S., Giauffret, C., Tardieu, F., Le Gouis, J., Langlade, N., Charcosset, A., Moing, A., Gibon, Y. , 2016. Fortune telling: metabolic markers of plant performance. Metabolomics 12, 158.
Fernandez, O., Urrutia, M., Berton, T., Bernillon, S., Deborde, C., Jacob, D., Maucourt, M., Maury, P., Duruflé, H., Gibon, Y., Langlade, NB, Moing, A., 2019. Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers. Metabolomics 15, 56. https://doi.org/10.1007/s11306-019-1515-4
Gascuel, Q., Bordat, A., Sallet, E., Pouilly, N., Carrere, S., Roux, F., Vincourt, P., Godiard, L., 2016a. Effector Polymorphisms of the Sunflower Downy Mildew Pathogen Plasmopara halstedii and Their Use to Identify Pathotypes from Field Isolates. PLoS ONE 11, e0148513. https://doi.org/10.1371/journal.pone.0148513
Gascuel, Q., Buendia, L., Pecrix, Y., Blanchet, N., Muños, S., Vear, F., Godiard, L., 2016b. RXLR and CRN effectors from the sunflower downy mildew pathogen Plasmopara halstedii induce hypersensitive-like responses in resistant sunflower lines. Forehead. Plant Sci. 7. https://doi.org/10.3389/fpls.2016.01887
Gody, L., Duruflé, H., Blanchet, N., Carré, C., Legrand, L., Mayjonade, B., Muños, S., Pomiès, L., Givry, S. de, Langlade, NB, Mangin, B., 2020a. Transcriptomic data of leaves from eight sunflower lines and their sixteen hybrids under water deficit. OCL 27, 48. https://doi.org/10.1051/ocl/2020044
Gosseau, F., Blanchet, N., Varès, D., Burger, P., Campergue, D., Colombet, C., Gody, L., Liévin, J.-F., Mangin, B., Tison, G., Vincourt, P., Casadebaig, P., Langlade, N., 2019. Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling. Forehead. Plant Sci. 9. https://doi.org/10.3389/fpls.2018.01908
Hübner, S., Bercovich, N., Todesco, M., Mandel, JR, Odenheimer, J., Ziegler, E., Lee, JS, Baute, GJ, Owens, GL, Grassa, CJ, Ebert, DP, Ostevik , KL, Moyers, BT, Yakimowski, S., Masalia, RR, Gao, L., Ćalić, I., Bowers, JE, Kane, NC, Swanevelder, DZH, Kubach, T., Muños, S., Langlade, NB, Burke, JM, Rieseberg, LH, 2019. Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance. Nature Plants 5, 54–62. https://doi.org/10.1038/s41477-018-0329-0
Layat, E., Leymarie, J., El-Maarouf-Bouteau, H., Caius, J., Langlade, N., Bailly, C., 2014. Translatome profiling in dormant and nondormant sunflower (Helianthus annuus) seeds highlights post - transcriptional regulation of germination. New Phytologist 204, 864–872.
Leroux, D., Rahmani, A., Jasson, S., Ventelon, M., Louis, F., Moreau, L., Mangin, B., 2014. Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design. Theoretical and applied genetics 127, 921–933.
Louarn, J., Boniface, M.-C., Pouilly, N., Velasco, L., Pérez-Vich, B., Vincourt, P., Muños, S., 2016. Sunflower Resistance to Broomrape (Orobanche cumana) Is Controlled by Specific QTLs for Different Parasitism Stages. Forehead. Plant Sci. 7. https://doi.org/10.3389/fpls.2016.00590
Luoni, SAB, Cenci, A., Moschen, S., Nicosia, S., Radonic, LM, Garcia, JS y, Langlade, NB, Vile, D., Rovere, CV, Fernandez, P., 2021. Genome- Wide Analysis of NAC Transcription Factors in Sunflower (Helianthus Annuus), Their Comparative Phylogenetic Analysis and Association With Leaf Senescence. BMC Plant Biology. https://doi.org/10.21203/rs.3.rs-860249/v1
Mangin, B., Bonnafous, F., Blanchet, N., Boniface, M.-C., Bret-Mestries, E., Carrère, S., Cottret, L., Legrand, L., Marage, G., Pegot-Espagnet, P., Munos, S., Pouilly, N., Vear, F., Vincourt, P., Langlade, NB, 2017a. Genomic Prediction of Sunflower Hybrids Oil Content. Forehead. Plant Sci. 8. https://doi.org/10.3389/fpls.2017.01633
Mangin, B., Casadebaig, P., Cadic, E., Blanchet, N., Boniface, M.-C., Carrère, S., Gouzy, J., Legrand, L., Mayjonade, B., Pouilly, N., André, T., Coque, M., Piquemal, J., Laporte, M., Vincourt, P., Muños, S., Langlade, NB, 2017b. Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modeling and genome-wide association. Plant, Cell & Environment 40, 2276–2291. https://doi.org/10.1111/pce.12961
Mangin, B., Casadebaig, P., Cadic, E., Blanchet, N., Boniface, M.-C., Carrère, S., Gouzy, J., Legrand, L., Mayjonade, B., Pouilly, N., André, T., Coque, M., Piquemal, J., Laporte, M., Vincourt, P., Muños, S., Langlade, NB, 2017c. Genetic control of oil yield plasticity to combined abiotic stresses using a joint approach of crop modeling and genome-wide association. Plant, Cell & Environment 40, 2276–2291.
Mangin, B., Pouilly, N., Boniface, M.-C., Langlade, NB, Vincourt, P., Vear, F., Muños, S., 2017d. Molecular diversity of sunflower populations maintained as genetic resources is affected by multiplication processes and breeding for major traits. Theor Appl Genet 130, 1099–1112. https://doi.org/10.1007/s00122-017-2872-x
Mangin, B., Rincent, R., Rabier, C.-E., Moreau, L., Goudemand-Dugue, E., 2019. Training set optimization of genomic prediction by means of EthAcc. PloS one 14, e0205629.
Mangin, B., Sandron, F., Henry, K., Devaux, B., Willems, G., Devaux, P., Goudemand, E., 2015. Breeding patterns and cultivated beets origins by genetic diversity and linkage disequilibrium analyzes . Theor. Appl. Broom. 128, 2255–2271. https://doi.org/10.1007/s00122-015-2582-1
Marchand, G., Huynh‐Thu, VA, Kane, NC, Arribat, S., Varès, D., Rengel, D., Balzergue, S., Rieseberg, LH, Vincourt, P., Geurts, P., Vignes , M., Langlade, NB, 2014. Bridging physiological and evolutionary time-scales in a gene regulatory network. New Phytologist 203, 685–696. https://doi.org/10.1111/nph.12818
Mayjonade, B., Gouzy, J., Donnadieu, C., Pouilly, N., Marande, W., Callot, C., Langlade, N., Muños, S., 2016. Extraction of high-molecular-weight genomics DNA for long-read sequencing of single molecules. BioTechniques 61, 203–205. https://doi.org/10.2144/000114460
Meimoun, P., Mordret, E., Langlade, NB, Balzergue, S., Arribat, S., Bailly, C., El-Maarouf-Bouteau, H., 2014. Is Gene Transcription Involved in Seed Dry After-Ripening ? PLoS ONE 9, e86442. https://doi.org/10.1371/journal.pone.0086442
Moschen, S., Marino, J., Nicosia, S., Higgins, J., Alseekh, S., Astigueta, F., Bengoa Luoni, S., Rivarola, M., Fernie, AR, Blanchet, N., Langlade, NB, Paniego, N., Fernández, P., Heinz, RA, 2019. Exploring gene networks in two sunflower lines with contrasting leaf senescence phenotype using a system biology approach. BMC Plant Biology 19, 446. https://doi.org/10.1186/s12870-019-2021-6
Pecrix, Y., Buendia, L., Penouilh-Suzette, C., Maréchaux, M., Legrand, L., Bouchez, O., Rengel, D., Gouzy, J., Cottret, L., Vear, F ., Godiard, L., 2019. Sunflower resistance to multiple downy mildew pathotypes revealed by recognition of conserved effectors of the oomycete Plasmopara halstedii. Plant J. 97, 730–748. https://doi.org/10.1111/tpj.14157
Penouilh-Suzette, C., Pomiès, L., Duruflé, H., Blanchet, N., Bonnafous, F., Dinis, R., Brouard, C., Gody, L., Grassa, C., Heudelot, X ., Laporte, M., Larroque, M., Marage, G., Mayjonade, B., Mangin, B., Givry, S. de, Langlade, NB, 2020. RNA expression dataset of 384 sunflower hybrids in field condition. OCL 27, 36. https://doi.org/10.1051/ocl/2020027
Rabier, C.-E., Barre, P., Asp, T., Charmet, G., Mangin, B., 2016. On the Accuracy of Genomic Selection. PLOS ONE 11, e0156086. https://doi.org/10.1371/journal.pone.0156086
Rabier, C.-E., Mangin, B., Grusea, S., 2019. On the accuracy in high-dimensional linear models and its application to genomic selection. Scandinavian Journal of Statistics 46, 289–313. https://doi.org/10.1111/sjos.12352
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