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Sanchez D, Allier A, Ben Sadoun S, Mary-Huard T, Bauland C, Palaffre C, Lagardère B, Madur D, Combes V, Melkior S, Bettinger L, Murigneux A, Moreau L, Charcosset A. Assessing the potential of genetic resource introduction into elite germplasm: a collaborative multiparental population for flint maize. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:19. [PMID: 38214870 PMCID: PMC10786986 DOI: 10.1007/s00122-023-04509-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 11/18/2023] [Indexed: 01/13/2024]
Abstract
KEY MESSAGE Implementing a collaborative pre-breeding multi-parental population efficiently identifies promising donor x elite pairs to enrich the flint maize elite germplasm. Genetic diversity is crucial for maintaining genetic gains and ensuring breeding programs' long-term success. In a closed breeding program, selection inevitably leads to a loss of genetic diversity. While managing diversity can delay this loss, introducing external sources of diversity is necessary to bring back favorable genetic variation. Genetic resources exhibit greater diversity than elite materials, but their lower performance levels hinder their use. This is the case for European flint maize, for which elite germplasm has incorporated only a limited portion of the diversity available in landraces. To enrich the diversity of this elite genetic pool, we established an original cooperative maize bridging population that involves crosses between private elite materials and diversity donors to create improved genotypes that will facilitate the incorporation of original favorable variations. Twenty donor × elite BC1S2 families were created and phenotyped for hybrid value for yield related traits. Crosses showed contrasted means and variances and therefore contrasted potential in terms of selection as measured by their usefulness criterion (UC). Average expected mean performance gain over the initial elite material was 5%. The most promising donor for each elite line was identified. Results also suggest that one more generation, i.e., 3 in total, of crossing to the elite is required to fully exploit the potential of a donor. Altogether, our results support the usefulness of incorporating genetic resources into elite flint maize. They call for further effort to create fixed diversity donors and identify those most suitable for each elite program.
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Affiliation(s)
- Dimitri Sanchez
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
| | - Antoine Allier
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
- Syngenta, 12 Chemin de L'Hobit, 31790, Saint-Sauveur, France
| | - Sarah Ben Sadoun
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
| | - Tristan Mary-Huard
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
- Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA-Paris Saclay, 91120, Palaiseau, France
| | - Cyril Bauland
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
| | - Carine Palaffre
- UE 0394 SMH, INRAE, 2297 Route de l'INRA, 40390, Saint-Martin-de-Hinx, France
| | - Bernard Lagardère
- UE 0394 SMH, INRAE, 2297 Route de l'INRA, 40390, Saint-Martin-de-Hinx, France
| | - Delphine Madur
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
| | - Valérie Combes
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
| | | | | | - Alain Murigneux
- Limagrain Europe, 28 Route d'Ennezat, 63720, Chappes, France
| | - Laurence Moreau
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France
| | - Alain Charcosset
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, 91190, Gif-Sur-Yvette, France.
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Affortit P, Ahmed MA, Grondin A, Delzon S, Carminati A, Laplaze L. Keep in touch: the soil-root hydraulic continuum and its role in drought resistance in crops. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:584-593. [PMID: 37549338 DOI: 10.1093/jxb/erad312] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
Drought is a major threat to food security worldwide. Recently, the root-soil interface has emerged as a major site of hydraulic resistance during water stress. Here, we review the impact of soil drying on whole-plant hydraulics and discuss mechanisms by which plants can adapt by modifying the properties of the rhizosphere either directly or through interactions with the soil microbiome.
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Affiliation(s)
- Pablo Affortit
- DIADE, IRD, CIRAD, Université de Montpellier, Montpellier, France
| | - Mutez Ali Ahmed
- Root-Soil Interaction, School of Life Science, Technical University of Munich, Freising, Germany
| | | | | | - Andrea Carminati
- Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
| | - Laurent Laplaze
- DIADE, IRD, CIRAD, Université de Montpellier, Montpellier, France
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Bouidghaghen J, Moreau L, Beauchêne K, Chapuis R, Mangel N, Cabrera-Bosquet L, Welcker C, Bogard M, Tardieu F. Robotized indoor phenotyping allows genomic prediction of adaptive traits in the field. Nat Commun 2023; 14:6603. [PMID: 37857601 PMCID: PMC10587076 DOI: 10.1038/s41467-023-42298-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 10/06/2023] [Indexed: 10/21/2023] Open
Abstract
Breeding for resilience to climate change requires considering adaptive traits such as plant architecture, stomatal conductance and growth, beyond the current selection for yield. Robotized indoor phenotyping allows measuring such traits at high throughput for speed breeding, but is often considered as non-relevant for field conditions. Here, we show that maize adaptive traits can be inferred in different fields, based on genotypic values obtained indoor and on environmental conditions in each considered field. The modelling of environmental effects allows translation from indoor to fields, but also from one field to another field. Furthermore, genotypic values of considered traits match between indoor and field conditions. Genomic prediction results in adequate ranking of genotypes for the tested traits, although with lesser precision for elite varieties presenting reduced phenotypic variability. Hence, it distinguishes genotypes with high or low values for adaptive traits, conferring either spender or conservative strategies for water use under future climates.
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Affiliation(s)
- Jugurta Bouidghaghen
- LEPSE, Univ Montpellier, INRAE, Montpellier, France
- ARVALIS, Chemin de la côte vieille, Baziège, France
| | - Laurence Moreau
- GQE-Le Moulon, INRAE, Université Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Katia Beauchêne
- ARVALIS, 45 Voie Romaine, Ouzouer-Le-Marché, Beauce La Romaine, France
| | | | - Nathalie Mangel
- ARVALIS, Station de recherche et d'expérimentation, Boigneville, France
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Vadez V, Messina CD, Carminati A. Combatting drought: a multi-dimensional challenge. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:4765-4769. [PMID: 37658757 DOI: 10.1093/jxb/erad301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Water will be a major limitation to food production in the 21st century, and drought issues already prevail in many parts of the world. Finding solutions to ensure that farmers harvest profitable crops, and secure food supplies for families and feed for animals that will provide for them through to the next season are urgent necessities. The Interdrought community has been addressing this issue for almost 30 years in a series of international conferences, characterized by a multi-disciplinary approach across the domains of molecular biology, physiology, genetics, agronomy, breeding, environmental and social sciences, policy, and systems modeling. This special issue presents papers from the 7th edition of the conference, the first to be held in Africa, that paid special attention to drought in a smallholder context, adding a 'system' dimension to the crop focus from the previous Interdrought events (Varshney et al., 2018; Hammer et al., 2021).
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Affiliation(s)
- Vincent Vadez
- Institute for Research and Development (IRD), DIADE Research Unit, University of Montpellier, 34394 Montpellier cedex 5, France
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India
- Centre d'Etudes Régional pour l'Amélioration de l'Adaptation à la Sècheresse (CERAAS), Campus ENSA, Thiès, Sénégal
| | - Carlos D Messina
- Department of Horticulture, University of Florida, Gainesville FL, USA
| | - Andrea Carminati
- Physics of Soils and Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
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Li Y, Tao F, Hao Y, Tong J, Xiao Y, He Z, Reynolds M. Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis. ANNALS OF BOTANY 2023; 131:503-519. [PMID: 36655618 PMCID: PMC10072080 DOI: 10.1093/aob/mcad003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/09/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND AND AIMS Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored. METHODS Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018-2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays. KEY RESULTS These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = -0.63, P < 0.01), flag leaf angle (r = -0.49, P < 0.01) and spike number per square metre (r = -0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars. CONCLUSIONS This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.
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Affiliation(s)
- Yibo Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Yuanfeng Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jingyang Tong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yonggui Xiao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | | | - Matthew Reynolds
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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Wang TC, Casadebaig P, Chen TW. More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:34. [PMID: 36897399 PMCID: PMC10006026 DOI: 10.1007/s00122-023-04264-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 10/10/2022] [Indexed: 06/18/2023]
Abstract
Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (Pi) was least affected among 11 SI. Pi was used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield or Pi. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in Pi; while light extinction coefficient and radiation use efficiency were more correlated with Pi than with yield. The high number of genotypes and environments required for studying Pi highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.
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Affiliation(s)
- Tien-Cheng Wang
- Section of Intensive Plant Food Systems, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.
- Institut für Gartenbauliche Produktionssysteme, Leibniz Universität Hannover, Hannover, Germany.
| | - Pierre Casadebaig
- INRAE, UMR AGIR, Université de Toulouse, 31320, Castanet-Tolosan, France
| | - Tsu-Wei Chen
- Section of Intensive Plant Food Systems, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.
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Cooper M, Messina CD. Breeding crops for drought-affected environments and improved climate resilience. THE PLANT CELL 2023; 35:162-186. [PMID: 36370076 PMCID: PMC9806606 DOI: 10.1093/plcell/koac321] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/01/2022] [Indexed: 05/12/2023]
Abstract
Breeding climate-resilient crops with improved levels of abiotic and biotic stress resistance as a response to climate change presents both opportunities and challenges. Applying the framework of the "breeder's equation," which is used to predict the response to selection for a breeding program cycle, we review methodologies and strategies that have been used to successfully breed crops with improved levels of drought resistance, where the target population of environments (TPEs) is a spatially and temporally heterogeneous mixture of drought-affected and favorable (water-sufficient) environments. Long-term improvement of temperate maize for the US corn belt is used as a case study and compared with progress for other crops and geographies. Integration of trait information across scales, from genomes to ecosystems, is needed to accurately predict yield outcomes for genotypes within the current and future TPEs. This will require transdisciplinary teams to explore, identify, and exploit novel opportunities to accelerate breeding program outcomes; both improved germplasm resources and improved products (cultivars, hybrids, clones, and populations) that outperform and replace the products in use by farmers, in combination with modified agronomic management strategies suited to their local environments.
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Affiliation(s)
| | - Carlos D Messina
- Horticultural Sciences Department, University of Florida, Gainesville, Florida 32611, USA
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Daviet B, Fernandez R, Cabrera-Bosquet L, Pradal C, Fournier C. PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time. PLANT METHODS 2022; 18:130. [PMID: 36482291 PMCID: PMC9730636 DOI: 10.1186/s13007-022-00961-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND High-throughput phenotyping platforms allow the study of the form and function of a large number of genotypes subjected to different growing conditions (GxE). A number of image acquisition and processing pipelines have been developed to automate this process, for micro-plots in the field and for individual plants in controlled conditions. Capturing shoot development requires extracting from images both the evolution of the 3D plant architecture as a whole, and a temporal tracking of the growth of its organs. RESULTS We propose PhenoTrack3D, a new pipeline to extract a 3D + t reconstruction of maize. It allows the study of plant architecture and individual organ development over time during the entire growth cycle. The method tracks the development of each organ from a time-series of plants whose organs have already been segmented in 3D using existing methods, such as Phenomenal [Artzet et al. in BioRxiv 1:805739, 2019] which was chosen in this study. First, a novel stem detection method based on deep-learning is used to locate precisely the point of separation between ligulated and growing leaves. Second, a new and original multiple sequence alignment algorithm has been developed to perform the temporal tracking of ligulated leaves, which have a consistent geometry over time and an unambiguous topological position. Finally, growing leaves are back-tracked with a distance-based approach. This pipeline is validated on a challenging dataset of 60 maize hybrids imaged daily from emergence to maturity in the PhenoArch platform (ca. 250,000 images). Stem tip was precisely detected over time (RMSE < 2.1 cm). 97.7% and 85.3% of ligulated and growing leaves respectively were assigned to the correct rank after tracking, on 30 plants × 43 dates. The pipeline allowed to extract various development and architecture traits at organ level, with good correlation to manual observations overall, on random subsets of 10-355 plants. CONCLUSIONS We developed a novel phenotyping method based on sequence alignment and deep-learning. It allows to characterise the development of maize architecture at organ level, automatically and at a high-throughput. It has been validated on hundreds of plants during the entire development cycle, showing its applicability on GxE analyses of large maize datasets.
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Affiliation(s)
- Benoit Daviet
- LEPSE, Univ Montpellier, INRAE, Institut Agro, Montpellier, France
| | - Romain Fernandez
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France
- CIRAD, INRAE, UMR AGAP Institut, Univ Montpellier, Institut Agro, 34398, Montpellier, France
| | | | - Christophe Pradal
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France.
- CIRAD, INRAE, UMR AGAP Institut, Univ Montpellier, Institut Agro, 34398, Montpellier, France.
- Inria & LIRMM, CNRS, Univ Montpellier, Montpellier, France.
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