Our current research focuses on four areas: genomewide selection, breeding schemes, targeted recombination, and sweet corn.
Genomewide selection (or genomic selection) exploits the availability of cheap and abundant markers. Phenotypic and single nucleotide polymorphism (SNP) marker data in a training population are used to develop a statistical model to predict performance for traits such as grain yield, moisture, and lodging. The accuracy of the genomewide predictions is assessed from a validation population, which has been phenotyped and genotyped.
If the predictions are sufficiently accurate, the statistical model is used to predict the performance of candidates in a test population, which has been genotyped but not yet phenotyped. We have found that wide-scale genomewide selection for hybrid yield among individual F2 plants leads to about 85% of the gains eventually achieved via phenotypic selection, but at less than 25% of the cost.
Technologies and resources that have become routinely used in commercial maize breeding include SNP markers, doubled haploids, embryo rescue, and year-round nurseries. We are investigating how such technologies and resources can be incorporated in practical breeding schemes. For example, we have found that two-cycle genomewide selection could lead to meaningful increases in genetic gains while keeping costs and the time required constant.
Targeted recombination for quantitative traits
Targeted recombination refers to the ability to have chromosomal recombinations just where a breeder wants them. Targeted recombinations can potentially be induced via a CRISPR-Cas system, or can be chosen among natural recombinations via procedures similar to marker-assisted backcrossing. The locations of targeted recombination can be estimated from genomewide marker effects for quantitative traits such as yield. Results in maize and in other crop species suggest that targeted recombination can double the amount of genetic gains. Empirical studies are being conducted to validate these large predicted gains.