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Mascher M, Marone MP, Schreiber M, Stein N. Are cereal grasses a single genetic system? NATURE PLANTS 2024; 10:719-731. [PMID: 38605239 DOI: 10.1038/s41477-024-01674-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 03/17/2024] [Indexed: 04/13/2024]
Abstract
In 1993, a passionate and provocative call to arms urged cereal researchers to consider the taxon they study as a single genetic system and collaborate with each other. Since then, that group of scientists has seen their discipline blossom. In an attempt to understand what unity of genetic systems means and how the notion was borne out by later research, we survey the progress and prospects of cereal genomics: sequence assemblies, population-scale sequencing, resistance gene cloning and domestication genetics. Gene order may not be as extraordinarily well conserved in the grasses as once thought. Still, several recurring themes have emerged. The same ancestral molecular pathways defining plant architecture have been co-opted in the evolution of different cereal crops. Such genetic convergence as much as cross-fertilization of ideas between cereal geneticists has led to a rich harvest of genes that, it is hoped, will lead to improved varieties.
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Affiliation(s)
- Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany.
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
| | - Marina Püpke Marone
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Mona Schreiber
- University of Marburg, Department of Biology, Marburg, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany.
- Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
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Berkner MO, Weise S, Reif JC, Schulthess AW. Genomic prediction reveals unexplored variation in grain protein and lysine content across a vast winter wheat genebank collection. FRONTIERS IN PLANT SCIENCE 2024; 14:1270298. [PMID: 38273944 PMCID: PMC10808176 DOI: 10.3389/fpls.2023.1270298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/31/2023] [Indexed: 01/27/2024]
Abstract
Globally, wheat (Triticum aestivum L.) is a major source of proteins in human nutrition despite its unbalanced amino acid composition. The low lysine content in the protein fraction of wheat can lead to protein-energy-malnutrition prominently in developing countries. A promising strategy to overcome this problem is to breed varieties which combine high protein content with high lysine content. Nevertheless, this requires the incorporation of yet undefined donor genotypes into pre-breeding programs. Genebank collections are suspected to harbor the needed genetic diversity. In the 1970s, a large-scale screening of protein traits was conducted for the wheat genebank collection in Gatersleben; however, this data has been poorly mined so far. In the present study, a large historical dataset on protein content and lysine content of 4,971 accessions was curated, strictly corrected for outliers as well as for unreplicated data and consolidated as the corresponding adjusted entry means. Four genomic prediction approaches were compared based on the ability to accurately predict the traits of interest. High-quality phenotypic data of 558 accessions was leveraged by engaging the best performing prediction model, namely EG-BLUP. Finally, this publication incorporates predicted phenotypes of 7,651 accessions of the winter wheat collection. Five accessions were proposed as donor genotypes due to the combination of outstanding high protein content as well as lysine content. Further investigation of the passport data suggested an association of the adjusted lysine content with the elevation of the collecting site. This publicly available information can facilitate future pre-breeding activities.
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Affiliation(s)
- Marcel O. Berkner
- Breeding Research Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Stephan Weise
- Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Jochen C. Reif
- Breeding Research Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Albert W. Schulthess
- Breeding Research Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
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Berkner MO, Schulthess AW, Zhao Y, Jiang Y, Oppermann M, Reif JC. Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:4391-4407. [PMID: 36182979 PMCID: PMC9734214 DOI: 10.1007/s00122-022-04227-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/17/2022] [Indexed: 06/16/2023]
Abstract
Genomic prediction of genebank accessions benefits from the consideration of additive-by-additive epistasis and subpopulation-specific marker effects. Wheat (Triticum aestivum L.) and other species of the Triticum genus are well represented in genebank collections worldwide. The substantial genetic diversity harbored by more than 850,000 accessions can be explored for their potential use in modern plant breeding. Characterization of these large number of accessions is constrained by the required resources, and this fact limits their use so far. This limitation might be overcome by engaging genomic prediction. The present study compared ten different genomic prediction approaches to the prediction of four traits, namely flowering time, plant height, thousand grain weight, and yellow rust resistance, in a diverse set of 7745 accession samples from Germany's Federal ex situ genebank at the Leibniz Institute of Plant Genetics and Crop Plant Research in Gatersleben. Approaches were evaluated based on prediction ability and robustness to the confounding influence of strong population structure. The authors propose the wide application of extended genomic best linear unbiased prediction due to the observed benefit of incorporating additive-by-additive epistasis. General and subpopulation-specific additive ridge regression best linear unbiased prediction, which accounts for subpopulation-specific marker-effects, was shown to be a good option if contrasting clusters are encountered in the analyzed collection. The presented findings reaffirm that the trait's genetic architecture as well as the composition and relatedness of the training set and test set are major driving factors for the accuracy of genomic prediction.
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Affiliation(s)
- Marcel O Berkner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Markus Oppermann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany.
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Renzi JP, Coyne CJ, Berger J, von Wettberg E, Nelson M, Ureta S, Hernández F, Smýkal P, Brus J. How Could the Use of Crop Wild Relatives in Breeding Increase the Adaptation of Crops to Marginal Environments? FRONTIERS IN PLANT SCIENCE 2022; 13:886162. [PMID: 35783966 PMCID: PMC9243378 DOI: 10.3389/fpls.2022.886162] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 05/11/2022] [Indexed: 06/01/2023]
Abstract
Alongside the use of fertilizer and chemical control of weeds, pests, and diseases modern breeding has been very successful in generating cultivars that have increased agricultural production several fold in favorable environments. These typically homogeneous cultivars (either homozygous inbreds or hybrids derived from inbred parents) are bred under optimal field conditions and perform well when there is sufficient water and nutrients. However, such optimal conditions are rare globally; indeed, a large proportion of arable land could be considered marginal for agricultural production. Marginal agricultural land typically has poor fertility and/or shallow soil depth, is subject to soil erosion, and often occurs in semi-arid or saline environments. Moreover, these marginal environments are expected to expand with ongoing climate change and progressive degradation of soil and water resources globally. Crop wild relatives (CWRs), most often used in breeding as sources of biotic resistance, often also possess traits adapting them to marginal environments. Wild progenitors have been selected over the course of their evolutionary history to maintain their fitness under a diverse range of stresses. Conversely, modern breeding for broad adaptation has reduced genetic diversity and increased genetic vulnerability to biotic and abiotic challenges. There is potential to exploit genetic heterogeneity, as opposed to genetic uniformity, in breeding for the utilization of marginal lands. This review discusses the adaptive traits that could improve the performance of cultivars in marginal environments and breeding strategies to deploy them.
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Affiliation(s)
- Juan Pablo Renzi
- Instituto Nacional de Tecnología Agropecuaria, Hilario Ascasubi, Argentina
- CERZOS, Departamento de Agronomía, Universidad Nacional del Sur (CONICET), Bahía Blanca, Argentina
| | | | - Jens Berger
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, Wembley, WA, Australia
| | - Eric von Wettberg
- Department of Plant and Soil Science, Gund Institute for Environment, University of Vermont, Burlington, VT, United States
- Department of Applied Mathematics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia
| | - Matthew Nelson
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, Wembley, WA, Australia
- The UWA Institute of Agriculture, University of Western Australia, Crawley, WA, Australia
| | - Soledad Ureta
- CERZOS, Departamento de Agronomía, Universidad Nacional del Sur (CONICET), Bahía Blanca, Argentina
| | - Fernando Hernández
- CERZOS, Departamento de Agronomía, Universidad Nacional del Sur (CONICET), Bahía Blanca, Argentina
| | - Petr Smýkal
- Department of Botany, Faculty of Science, Palacký University, Olomouc, Czechia
| | - Jan Brus
- Department of Geoinformatics, Faculty of Sciences, Palacký University, Olomouc, Czechia
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Monnot S, Desaint H, Mary-Huard T, Moreau L, Schurdi-Levraud V, Boissot N. Deciphering the Genetic Architecture of Plant Virus Resistance by GWAS, State of the Art and Potential Advances. Cells 2021; 10:3080. [PMID: 34831303 PMCID: PMC8625838 DOI: 10.3390/cells10113080] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 11/03/2021] [Accepted: 11/04/2021] [Indexed: 01/04/2023] Open
Abstract
Growing virus resistant varieties is a highly effective means to avoid yield loss due to infection by many types of virus. The challenge is to be able to detect resistance donors within plant species diversity and then quickly introduce alleles conferring resistance into elite genetic backgrounds. Until now, mainly monogenic forms of resistance with major effects have been introduced in crops. Polygenic resistance is harder to map and introduce in susceptible genetic backgrounds, but it is likely more durable. Genome wide association studies (GWAS) offer an opportunity to accelerate mapping of both monogenic and polygenic resistance, but have seldom been implemented and described in the plant-virus interaction context. Yet, all of the 48 plant-virus GWAS published so far have successfully mapped QTLs involved in plant virus resistance. In this review, we analyzed general and specific GWAS issues regarding plant virus resistance. We have identified and described several key steps throughout the GWAS pipeline, from diversity panel assembly to GWAS result analyses. Based on the 48 published articles, we analyzed the impact of each key step on the GWAS power and showcase several GWAS methods tailored to all types of viruses.
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Affiliation(s)
- Severine Monnot
- INRAE, Génétique et Amélioration des Fruits et Légumes (GAFL), 84143 Montfavet, France
- Bayer Crop Science, Chemin de Roque Martine, 13670 Saint-Andiol, France
| | - Henri Desaint
- INRAE, Génétique et Amélioration des Fruits et Légumes (GAFL), 84143 Montfavet, France
| | - Tristan Mary-Huard
- INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, Université Paris-Saclay, Ferme du Moulon, 91190 Gif-sur-Yvette, France
- Mathématiques et Informatique Appliquées (MIA)-Paris, INRAE, AgroParisTech, Université Paris-Saclay, 75231 Paris, France
| | - Laurence Moreau
- INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution-Le Moulon, Université Paris-Saclay, Ferme du Moulon, 91190 Gif-sur-Yvette, France
| | | | - Nathalie Boissot
- INRAE, Génétique et Amélioration des Fruits et Légumes (GAFL), 84143 Montfavet, France
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