1a.Objectives (from AD-416)
1. Select progeny based on genomic selection (GS) and phenotypic selection and compare their performance in subsequent field trials.
2. Assess the ability of GS to predict the true breeding value of a parent
3. Determine whether a trained GS model maintains accuracy over cycles of breeding.
4. Use simulations to assess scenarios for the introduction and implementation of GS in a breeding program to optimize short- and long-term success over cycles of GS.
1b.Approach (from AD-416)
Cooperating PI’s will run field experiments on sets of progeny to obtain phenotypic data; they will also extract DNA and obtain marker data. We will analyze these data using several genomic selection methods to generate predictions of breeding and genetic values based on marker data. In parallel, we will use these data and other data available from historical trials to estimate breeding and genetic values directly from phenotype and pedigree data. We will then correlate predictions with directly observed data to evaluate the accuracy of genomic selection.
An important component of this project is to determine through simulation under what conditions genomic selection will be favorable for applied plant breeding. This has required the development of a software framework for implementing and simulating genomic selection. We have programmed this framework in R. As a first product of this work, we have simulated gains from long-term genomic selection and shown that the marker data used to make genomic predictions of the performance and breeding value of a line can also be used to maintain genetic diversity and favorable alleles in the breeding program. This approach increases long-term gain while only marginally decreasing short-term gain. A manuscript on this issue has been accepted for publication.