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

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Title Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program
 
Creator Platten, John Damien
Fritsche-Neto, Roberto
 
Subject breeding
genomics
selection
quality
quantitative trait loci
simulation models
 
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.
 
Date 2022-07-06
2023-01-06T09:22:18Z
2023-01-06T09:22:18Z
 
Type Journal Article
 
Identifier Platten, John Damien and Fritsche-Neto, Roberto. 2022. Optimizing QTL introgression via stochastic simulations: An example of the IRRI rice breeding program. Research Square
2693-5015
https://hdl.handle.net/10568/126653
https://doi.org/10.21203/rs.3.rs-1780978/v1
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format 22 p.
application/pdf
 
Source Research Square