Abstract
Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the breeding cycle. Gain can also be increased through higher selection intensities, as the size of the population available for selection can be increased by predicting performance of non‐phenotyped, but genotyped, lines. This paper demonstrates the application of genomic prediction in a sorghum [ Sorghum bicolor (L.) Moench] breeding program and compares different genomic prediction models incorporating relationship information derived from molecular markers and pedigree information. In cross‐validation, the models using marker‐based relationships had higher selection accuracy than the selection accuracy for models that used pedigree‐based relationships. It was demonstrated that genotypes that have not been included in the trials could be predicted quite accurately using marker information alone. The accuracy of prediction declined as the genomic relationship of the predicted individual to the training population declined. We also demonstrate that the accuracy of genomic breeding values from the prediction error variance derived from the mixed model equations is a useful indicator of the accuracy of prediction. This will be useful to plant breeders, as the accuracy of the genomic predictions can be assessed with confidence before phenotypes are available. Four distinct environments were studied and shown to perform very differently with respect to the accuracy of predictions and the composition of estimated breeding values. This paper shows that there is considerable potential for sorghum breeding programs to benefit from the implementation of genomic selection.
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Claims 6
Claim · model-written summary
Marker-based relationship models had higher selection accuracy than pedigree-based models.
- Outcome
- selection accuracye0
- Direction
- highere0
- Comparator
- models that used pedigree‐based relationshipse0
Not reportedTaxon
Verbatim
e0“In cross‐validation, the models using marker‐based relationships had higher selection accuracy than the selection accuracy for models that used pedigree‐based relationships.”
Claim · model-written summary
Marker data alone predicted sorghum genotypes absent from trials quite accurately.
Not reportedTaxonValue
Verbatim
e0“It was demonstrated that genotypes that have not been included in the trials could be predicted quite accurately using marker information alone.”
Claim · model-written summary
Prediction accuracy declined with decreasing genomic relatedness to the training population.
- Outcome
- accuracy of predictione0
- Direction
- declinede0
- Comparator
- genomic relationship of the predicted individual to the training populatione0
Not reportedTaxon
Verbatim
e0“The accuracy of prediction declined as the genomic relationship of the predicted individual to the training population declined.”
Claim · model-written summary
Accuracy from prediction error variance was a useful indicator of genomic prediction accuracy.
- Outcome
- accuracy of predictione0
- Comparator
- accuracy of genomic breeding values from the prediction error variancee0
Not reportedTaxon
Verbatim
e0“the accuracy of genomic breeding values from the prediction error variance derived from the mixed model equations is a useful indicator of the accuracy of prediction.”
Claim · model-written summary
Four sorghum environments differed substantially in prediction accuracy and estimated breeding value composition.
- Outcome
- accuracy of predictions and the composition of estimated breeding valuese0
- Direction
- very differentlye0
- Setting
- Four distinct environmentse0
Not reportedTaxon
Verbatim
e0“Four distinct environments were studied and shown to perform very differently with respect to the accuracy of predictions and the composition of estimated breeding values.”
Claim · model-written summary
The authors see considerable potential for genomic selection in sorghum breeding.
SorghumOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“This paper shows that there is considerable potential for sorghum breeding programs to benefit from the implementation of genomic selection.”