TORONTO (PRWEB) January 14, 2019
Forward genetic screens provide a powerful tool to identify genes or genetic networks that contribute to specific biological phenotypes or diseases and therefore hold great potential for elucidating gene function and revealing therapeutic targets for diseases. The advent of CRISPR-Cas technology has revolutionized genome editing in higher eukaryotes and enables efficient gene manipulation in mammalian cells. CRISPR guide-RNA libraries allow facile generation of a pool of genetically perturbed cells and its application in genetic screens has marked a major breakthrough for functional genomics in mammalian cells.
Using genome wide CRISPR-Cas9 knockout libraries, the Moffat Lab has screened various human cell lines to reveal a set of core fitness genes required to sustain proliferation, and context-dependent fitness genes that are essential only in a specific genotype uncovering novel genetic dependencies. Accompanying these screens, the Moffat Lab has developed statistical scoring algorithms like the Bayesian Analysis of Gene Essentiality (“BAGEL”) to identify fitness genes, as well as gold standard reference gene sets that allow us validate screening performance. Using an optimized screening workflow, they are currently applying CRISPR-Cas9 technology to construct a genetic interaction network for a reference human cell line (HAP1) for functional annotation of the human genome based on mutant query screens.
Join Michael Aregger, PhD and Keith Lawson, MD – from the Moffat lab at the University of Toronto, in a live session on Thursday, February 7, 2019 at 11am EST (4pm GMT) to learn:
- How to design and perform genome-wide pooled CRISPR screens in mammalian cells
- To use the gold standard essential and non-essential reference gene sets to control screen performance
- Experimental approaches to reveal genetic interactions in isogenic CRISPR modified human cells lines
For more information or to register for this event, visit Using CRISPR-Cas Screens to Reveal Fitness Genes and to Map Genetic Interactions.
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