Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation

Posted by Carelia Juarez on , in Journal Articles

Published in Crop Science, 2014

 Hickey, J.M.Dreisigacker, S.Crossa, J.Hearne, S.Babu, R.Prasanna, B.M.Grondona, M.Zambelli. A.Windhausen, V.S.Mathews, K.Gorjanc, G. 

Genomic selection offers great potential to increase the rate of genetic improvement in plant breeding programs. This research used simulation to evaluate the effectiveness of different strategies for genotyping and phenotyping in order to enable genomic selection in early generation individuals (e.g., F2), in breeding programs involving bi-parental or similar (e.g. back cross or top cross) populations. By using phenotypes that were previously collected in other bi-parental populations selection decisions could be made without waiting for phenotypes that pertain directly to the selection candidate to be collected, a process that would take at least three growing seasons. If these phenotypes were collected in bi-parental populations that were closely related to the selection candidates only a small number of markers (e.g. 200-500) and a small number of phenotypes (e.g. 1000) were needed to achieve effective accuracy of estimated breeding values. If these phenotypes were collected in bi-parental populations that were not closely related to the selection candidates, as many as 10000 markers and 5000 to 20000 phenotypes were needed. Increasing marker density beyond 10000 markers did not show benefit and in some scenarios reduced the accuracy of prediction. This study provides a guide, enabling resource allocation to be optimized between genotyping and phenotyping investment dependent on the population under development.


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