Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program

A key limitation in the ability of breeding programs to leverage benefits of major-gene marker-assisted selection is the availability of those genes in appropriate elite germplasm. In this context, our study compared three strategies to develop new recipients for QTL introgression (Background recove...

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Autores principales: Platten, John Damien, Fritsche-Neto, Roberto
Formato: Preprint
Lenguaje:Inglés
Publicado: Research Square Platform LLC 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/126653
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author Platten, John Damien
Fritsche-Neto, Roberto
author_browse Fritsche-Neto, Roberto
Platten, John Damien
author_facet Platten, John Damien
Fritsche-Neto, Roberto
author_sort Platten, John Damien
collection Repository of Agricultural Research Outputs (CGSpace)
description A key limitation in the ability of breeding programs to leverage benefits of major-gene marker-assisted selection is the availability of those genes in appropriate elite germplasm. In this context, our study compared three strategies to develop new recipients for QTL introgression (Background recovery (BG), Selective sweep (SS), and Breeding values (BV)) in a short-term breeding program (over five breeding cycles). Furthermore, we evaluated two different numbers of recipients (10 and 20) in the introgression process and how they influence the population performance and the QTL fixation over cycles. Finally, we used rice as a model of a self- pollinated crop and implemented stochastic simulations. Each strategy was simulated and replicated 40 times. Regardless of the selection strategy used, the QTL introgression resulted in substantial penalties in yield performance. However, introducing fewer new parents to the augmentation process minimized this effect. Conversely, the time required to achieve fixation of target QTLs showed substantial differences, with selection for BV during augmentation out-performing other methods. Overall, the BV_10 strategy (10 parents selected based on genomic estimated breeding values) displayed the best trade-off between reduced penalty from introducing new QTLs with a reasonable speed at which those QTLs can achieve fixation over subsequent breeding cycles.
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spelling CGSpace1266532025-11-12T04:58:38Z Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program Platten, John Damien Fritsche-Neto, Roberto breeding genomics selection quality quantitative trait loci simulation models A key limitation in the ability of breeding programs to leverage benefits of major-gene marker-assisted selection is the availability of those genes in appropriate elite germplasm. In this context, our study compared three strategies to develop new recipients for QTL introgression (Background recovery (BG), Selective sweep (SS), and Breeding values (BV)) in a short-term breeding program (over five breeding cycles). Furthermore, we evaluated two different numbers of recipients (10 and 20) in the introgression process and how they influence the population performance and the QTL fixation over cycles. Finally, we used rice as a model of a self- pollinated crop and implemented stochastic simulations. Each strategy was simulated and replicated 40 times. Regardless of the selection strategy used, the QTL introgression resulted in substantial penalties in yield performance. However, introducing fewer new parents to the augmentation process minimized this effect. Conversely, the time required to achieve fixation of target QTLs showed substantial differences, with selection for BV during augmentation out-performing other methods. Overall, the BV_10 strategy (10 parents selected based on genomic estimated breeding values) displayed the best trade-off between reduced penalty from introducing new QTLs with a reasonable speed at which those QTLs can achieve fixation over subsequent breeding cycles. 2022-07-06 2023-01-06T09:22:18Z 2023-01-06T09:22:18Z Preprint https://hdl.handle.net/10568/126653 en Open Access application/pdf Research Square Platform LLC Platten, John Damien and Fritsche-Neto, Roberto. 2022. Optimizing QTL introgression via stochastic simulations: An example of the IRRI rice breeding program. Research Square
spellingShingle breeding
genomics
selection
quality
quantitative trait loci
simulation models
Platten, John Damien
Fritsche-Neto, Roberto
Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
title Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
title_full Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
title_fullStr Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
title_full_unstemmed Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
title_short Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
title_sort optimizing qtl introgression via stochastic simulations an example of the irri rice breeding program
topic breeding
genomics
selection
quality
quantitative trait loci
simulation models
url https://hdl.handle.net/10568/126653
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