Systematic identification of genetic interactions in plants using a combinatorial CRISPR screening pipeline (3S005320)
Genetic interaction occurs when a geneU+2019s effect is modified by one or several other genes. Redundancy is one type of interaction and it interferes with investigations into gene function as mutations in single genes do not always result in clear or obvious phenotypes. Genetic interactors have been systematically identified in yeast and mammals, but only a few experiments have been reported in plants. This is due to a lack of high-throughput screens capable of finding genetic interactions in plant systems. With the advent of CRISPR screens, new possibilities have arisen. In a CRISPR screen, a population is mutagenized by targeting specific genes of interest and then screened for a specific phenotype of interest. In this project, I will automate and optimize a CRISPR screening pipeline to find genetic interactions in plants. I will develop a bioinformatics tool that simultaneously designs guides and primers for downstream genotyping. I will then perform a CRISPR screen on 50 members of the MAP3K gene family with different numbers of guides per vector to determine an optimal screen size. I will use the dataset to develop tests for genetic interactions. In the final phase, B. napus genes with predicted interactions that influence yield traits will be screened using Arabidopsis as a proxy. In the end, I will have established an optimized pipeline that will enable researchers to rapidly screen for genetic interactions in their plant system.