Genomewide Predictions of Maize Performance
Genomewide predictions allow the evaluation of maize lines or hybrids without field testing (phenotyping) of the lines or hybrids themselves. In particular, genomewide marker effects are estimated from a training population that has been previously genotyped and phenotyped. These marker effects are then used to assess the performance of new lines or hybrids that have been genotyped, but not yet phenotyped. Genomewide predictions therefore leverage the lower costs of genotyping (about $15 per line or hybrid) than of phenotyping (about $120 per line or hybrid). Since 2011, the Bernardo research group has been given access by Monsanto to about $25 million worth of phenotypic and marker datasets from its own maize breeding program. These datasets have allowed the group to investigate ways to optimize genomewide predictions in maize breeding. Research efforts are now focusing not only on predicting performance averaged across environments, but also in specific environments. The scale of the datasets (969 populations, >4 million phenotypic data points, > 11 million marker data points, and environmental covariables on 432 year-location combinations) has necessitated the use of high-performance computing resources.
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