Targeted engineering of quantitative traits in plants.

Our ability to develop novel beneficial crop traits through traditional molecular breeding has significantly improved over the last decade, however, the ability to maintain this trajectory is limited by allelic diversity. While genetic variation at coding sequences has been heavily exploited for crop improvement, most quantitative traits reside in mutations at non-coding regulatory regions. My project aims to perform a computational analysis of cereal genomic and epigenomic data to identify the regulatory regions that underpin desirable agronomic traits. Once identified, CRISPR mutagenesis using a multiplexed approach will allow the modification of multiple target sites to thus engineer greater targeted variation in gene expression resulting in novel phenotypes. Lines displaying enhanced phenotypic variation for desirable agricultural traits -primarily yield- will be selected to investigate the relationship between the temporospatial regulation of defined regulatory networks and trait performance.