Genetic mapping the process of determining the genes that underlie a trait of interest is essential to medical genetics, and has played a fundamental role in our understanding of genetic diseases, pathogen virulence, and other topics across the entire range of biological phenomena. I am proposing a novel strategy to rapidly map genetic variants underlying important traits. This strategy involves generating variant genotypes from a single cell through loss-of-heterozygosity resulting from CRISPR, a genome-editing technology. The panel of variant cells can be used for mapping in much the same way as is done in linkage analysis. However, because the genomic rearrangements resulting from CRISPR will be targeted to precise regions of the genome, the method can provide arbitrarily high mapping resolution through iterative nested mapping panels, leading to the rapid identification of the genes and variants underlying the trait of interest. In theory, this method could enable the mapping of disease genes from single patients. The method will first be developed in the model organism Saccharomyces cerevisiae, which has been an essential test bed for fundamental tools and concepts in genetics. After this proof-of-principle experiment, the method will be applied to human cells to uncover genes influencing cancer drug effectiveness. This mapping approach will be further applied to uncover genetic variants that control other genes' expression, which could illuminate the mechanism through which genetic variants cause disease. Once developed, the ability to map genetic variants from a single individual will be extremely useful in myriad future mapping efforts.
The goal of medical genetics is to identify the genes that underlie diseases, in order to predict individuals' disease risks and suggest targets for drug development. We propose a completely novel strategy to identify causative genes that will work with extremely high resolution and speed.
| Sadhu, Meru J; Bloom, Joshua S; Day, Laura et al. (2018) Highly parallel genome variant engineering with CRISPR-Cas9. Nat Genet 50:510-514 |
| Forsberg, Simon K G; Bloom, Joshua S; Sadhu, Meru J et al. (2017) Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast. Nat Genet 49:497-503 |
| Sadhu, Meru J; Bloom, Joshua S; Day, Laura et al. (2016) CRISPR-directed mitotic recombination enables genetic mapping without crosses. Science 352:1113-6 |
