Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations
This study compared three strategies to develop new recipients for quantitative trait loci (QTL) introgression (background recovery [BG], selective sweep [SS] and breeding value [BV]) in a short-term rice breeding programme (over five breeding cycles). Furthermore, we evaluated two different numbers...
| Autores principales: | , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2023
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/132706 |
| _version_ | 1855530293316812800 |
|---|---|
| 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 | This study compared three strategies to develop new recipients for quantitative trait loci (QTL) introgression (background recovery [BG], selective sweep [SS] and breeding value [BV]) in a short-term rice breeding programme (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 the International Rice Research Institute (IRRI) rice breeding framework as the model to perform the stochastic simulations. Each strategy was simulated and replicated 100 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 outperforming other methods. Overall, the BV_10 strategy (10 parents selected based on genomic estimated BV) 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. |
| format | Journal Article |
| id | CGSpace132706 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace1327062025-12-08T10:11:39Z Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations Platten, John Damien Fritsche-Neto, Roberto gene transfer genomics genomic selection simulation This study compared three strategies to develop new recipients for quantitative trait loci (QTL) introgression (background recovery [BG], selective sweep [SS] and breeding value [BV]) in a short-term rice breeding programme (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 the International Rice Research Institute (IRRI) rice breeding framework as the model to perform the stochastic simulations. Each strategy was simulated and replicated 100 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 outperforming other methods. Overall, the BV_10 strategy (10 parents selected based on genomic estimated BV) 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. 2023-08 2023-11-03T13:20:36Z 2023-11-03T13:20:36Z Journal Article https://hdl.handle.net/10568/132706 en Open Access application/pdf Wiley Platten, J. D., & Fritsche-Neto, R. (2023). Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations. PlantBreeding,142(4), 439–448. https://doi.org/10.1111/pbr.13118448 |
| spellingShingle | gene transfer genomics genomic selection simulation Platten, John Damien Fritsche-Neto, Roberto Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
| title | Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
| title_full | Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
| title_fullStr | Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
| title_full_unstemmed | Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
| title_short | Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations |
| title_sort | optimizing quantitative trait loci introgression in elite rice germplasms comparing methods and population sizes to develop new recipients via stochastic simulations |
| topic | gene transfer genomics genomic selection simulation |
| url | https://hdl.handle.net/10568/132706 |
| work_keys_str_mv | AT plattenjohndamien optimizingquantitativetraitlociintrogressioninelitericegermplasmscomparingmethodsandpopulationsizestodevelopnewrecipientsviastochasticsimulations AT fritschenetoroberto optimizingquantitativetraitlociintrogressioninelitericegermplasmscomparingmethodsandpopulationsizestodevelopnewrecipientsviastochasticsimulations |