New approaches to maximise gain and genetic diversity in breeding programs

This project aims to use simulation approaches to explore the expected performance of selection using haplotype stacking approaches. Haplotype stacking approaches are a family of algorithms for breeding that use the haplotype structure of a breeding population to make breeding decisions that would 'stack', or accumulate, beneficial haplotype blocks in descendant genotypes. The performance of haplotype stacking approaches would depend on how they could be adapted to the presence and distribution of desirable haplotype blocks in the population and to breeding constraints. The development of technologies to influence recombination rate or recombination locations in meiosis is a current area of research, and once available, the interactions of such technologies with haplotype stacking techniques would be another important factor in identifying where haplotype stacking approaches are valuable, because the low natural likelihood of important recombinations for stacking is a major constraint on rate of stacking of desirable haplotypes.
In this project, modified constraints for haplotype stacking algorithms to suit different scenarios will be explored. The project will also investigate methods of incorporating increased recombination rate or targeted recombination technologies into haplotype stacking selection approaches, under simple and more complex genetic architectures.