The project consists of three parts: in the first part, we will develop methodology for determining haplotypes in a breeding pool (containing both distantly related genotypes and genotypes with direct (offspring) relationships). Using state-of-the art methods and to be developed new methods, an integrated bioinformatics and quantitative genetics approach will be followed to determine discrete and probabilistic haplotypes from sequencing data and limit the number of probable solutions by including pedigree relationships and observed allele frequencies and/or by estimating the most probable haplotype using imputation strategies from either whole genome sequencing (WGS) or reduced complexity sequencing. The estimated haplotypes will be added to an atlas of haplotypes, which will be used in future iterations of haplotyping and to improve haplotype-based predictions of traits. In the second part, methods are developed to optimally use haplotypes to enable prediction of traits and selection in breeding programs, both for traits determined by few large-effect loci and for traits determined by a larger number of smaller effect loci. Factors influencing the accuracy of predicting the phenotype from the haplotypes will be studied using simulations where these factors can be varied at will, while an experimental dataset is used to validate the method for practical use and to guide the improvement of the haplotyping. In the third part, a visualization tool for the detected haplotypes is developed that allows accessions from the breeding pool to be assessed by combining the predicted haplotypes in these accessions with observed phenotypes or predicted breeding values for traits. This visualization tool can be used for selection in a specific set of germplasm in a running breeding program.
|Effective start/end date||1/01/21 → 1/03/25|