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Villar-Hernández BDJ, Dreisigacker S, Crespo L, Pérez-Rodríguez P, Pérez-Elizalde S, Toledo F, Crossa J. A Bayesian optimization R package for multitrait parental selection. THE PLANT GENOME 2024; 17:e20433. [PMID: 38385985 DOI: 10.1002/tpg2.20433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 12/26/2023] [Accepted: 01/02/2024] [Indexed: 02/23/2024]
Abstract
Selecting and mating parents in conventional phenotypic and genomic selection are crucial. Plant breeding programs aim to improve the economic value of crops, considering multiple traits simultaneously. When traits are negatively correlated and/or when there are missing records in some traits, selection becomes more complex. To address this problem, we propose a multitrait selection approach using the Multitrait Parental Selection (MPS) R package-an efficient tool for genetic improvement, precision breeding, and conservation genetics. The package employs Bayesian optimization algorithms and three loss functions (Kullback-Leibler, Energy Score, and Multivariate Asymmetric Loss) to identify parental candidates with desirable traits. The software's functionality includes three main functions-EvalMPS, FastMPS, and ApproxMPS-catering to different data availability scenarios. Through the presented application examples, the MPS R package proves effective in multitrait genomic selection, enabling breeders to make informed decisions and achieve strong performance across multiple traits.
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Affiliation(s)
- Bartolo de J Villar-Hernández
- International Maize and Wheat Improvement Center (CIMMYT), Estado de México, México
- Colegio de Postgraduados, Montecillo, Estado de México, 56230, México
| | - Susanne Dreisigacker
- International Maize and Wheat Improvement Center (CIMMYT), Estado de México, México
| | - Leo Crespo
- International Maize and Wheat Improvement Center (CIMMYT), Estado de México, México
| | | | | | - Fernando Toledo
- International Maize and Wheat Improvement Center (CIMMYT), Estado de México, México
| | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Estado de México, México
- Colegio de Postgraduados, Montecillo, Estado de México, 56230, México
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Villar-Hernández BDJ, Pérez-Elizalde S, Martini JWR, Toledo F, Perez-Rodriguez P, Krause M, García-Calvillo ID, Covarrubias-Pazaran G, Crossa J. Application of multi-trait Bayesian decision theory for parental genomic selection. G3-GENES GENOMES GENETICS 2021; 11:6104551. [PMID: 33693601 PMCID: PMC8022966 DOI: 10.1093/g3journal/jkab012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/04/2021] [Indexed: 12/01/2022]
Abstract
In all breeding programs, the decision about which individuals to select and intermate to form the next selection cycle is crucial. The improvement of genetic stocks requires considering multiple traits simultaneously, given that economic value and net genetic merits depend on many traits; therefore, with the advance of computational and statistical tools and genomic selection (GS), researchers are focusing on multi-trait selection. Selection of the best individuals is difficult, especially in traits that are antagonistically correlated, where improvement in one trait might imply a reduction in other(s). There are approaches that facilitate multi-trait selection, and recently a Bayesian decision theory (BDT) has been proposed. Parental selection using BDT has the potential to be effective in multi-trait selection given that it summarizes all relevant quantitative genetic concepts such as heritability, response to selection and the structure of dependence between traits (correlation). In this study, we applied BDT to provide a treatment for the complexity of multi-trait parental selection using three multivariate loss functions (LF), Kullback–Leibler (KL), Energy Score, and Multivariate Asymmetric Loss (MALF), to select the best-performing parents for the next breeding cycle in two extensive real wheat data sets. Results show that the high ranking lines in genomic estimated breeding value (GEBV) for certain traits did not always have low values for the posterior expected loss (PEL). For both data sets, the KL LF gave similar importance to all traits including grain yield. In contrast, the Energy Score and MALF gave a better performance in three of four traits that were different than grain yield. The BDT approach should help breeders to decide based not only on the GEBV per se of the parent to be selected, but also on the level of uncertainty according to the Bayesian paradigm.
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Affiliation(s)
- Bartolo de Jesús Villar-Hernández
- Colegio de Postgraduados, Montecillos, Edo. de Mexico, CP 56264,Mexico.,Universidad Autonoma de Coahuila, Saltillo, CP 25280, Mexico
| | | | - Johannes W R Martini
- International Maize and Wheat Improvement Center (CIMMYT). Km 45 Carretera México-Veracruz, El Batán Km. 45, CP 56237 Mexico
| | - Fernando Toledo
- International Maize and Wheat Improvement Center (CIMMYT). Km 45 Carretera México-Veracruz, El Batán Km. 45, CP 56237 Mexico
| | - P Perez-Rodriguez
- Colegio de Postgraduados, Montecillos, Edo. de Mexico, CP 56264,Mexico
| | - Margaret Krause
- International Maize and Wheat Improvement Center (CIMMYT). Km 45 Carretera México-Veracruz, El Batán Km. 45, CP 56237 Mexico
| | | | - Giovanny Covarrubias-Pazaran
- International Maize and Wheat Improvement Center (CIMMYT). Km 45 Carretera México-Veracruz, El Batán Km. 45, CP 56237 Mexico
| | - José Crossa
- Colegio de Postgraduados, Montecillos, Edo. de Mexico, CP 56264,Mexico.,International Maize and Wheat Improvement Center (CIMMYT). Km 45 Carretera México-Veracruz, El Batán Km. 45, CP 56237 Mexico
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Michel S, Löschenberger F, Ametz C, Pachler B, Sparry E, Bürstmayr H. Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:1745-1760. [PMID: 30810763 PMCID: PMC6531418 DOI: 10.1007/s00122-019-03312-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 02/15/2019] [Indexed: 05/10/2023]
Abstract
KEY MESSAGE Large genetic improvement can be achieved by simultaneous genomic selection for grain yield and protein content when combining different breeding strategies in the form of selection indices. Genomic selection has been implemented in many national and international breeding programmes in recent years. Numerous studies have shown the potential of this new breeding tool; few have, however, taken the simultaneous selection for multiple traits into account that is though common practice in breeding programmes. The simultaneous improvement in grain yield and protein content is thereby a major challenge in wheat breeding due to a severe negative trade-off. Accordingly, the potential and limits of multi-trait selection for this particular trait complex utilizing the vast phenotypic and genomic data collected in an applied wheat breeding programme were investigated in this study. Two breeding strategies based on various genomic-selection indices were compared, which (1) aimed to select high-protein genotypes with acceptable yield potential and (2) develop high-yielding varieties, while maintaining protein content. The prediction accuracy of preliminary yield trials could be strongly improved when combining phenotypic and genomic information in a genomics-assisted selection approach, which surpassed both genomics-based and classical phenotypic selection methods both for single trait predictions and in genomic index selection across years. The employed genomic selection indices mitigated furthermore the negative trade-off between grain yield and protein content leading to a substantial selection response for protein yield, i.e. total seed nitrogen content, which suggested that it is feasible to develop varieties that combine a superior yield potential with comparably high protein content, thus utilizing available nitrogen resources more efficiently.
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Affiliation(s)
- Sebastian Michel
- Department of Agrobiotechnology, IFA-Tulln, University of Natural Resources and Life Sciences Vienna, Konrad-Lorenz-Str. 20, 3430, Tulln, Austria.
| | | | - Christian Ametz
- Saatzucht Donau GesmbH & CoKG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria
| | - Bernadette Pachler
- Saatzucht Donau GesmbH & CoKG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria
| | - Ellen Sparry
- C&M Seeds, 6180 5th Line, Palmerston, ON, N0G 2P0, Canada
| | - Hermann Bürstmayr
- Department of Agrobiotechnology, IFA-Tulln, University of Natural Resources and Life Sciences Vienna, Konrad-Lorenz-Str. 20, 3430, Tulln, Austria
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