- Heo, Seok-Jin;
- Enriquez, Lauren;
- Federman, Scot;
- Chang, Amy;
- Mace, Rachel;
- Shevade, Kaivalya;
- Nguyen, Phuong;
- Litterman, Adam;
- Shafer, Shawn;
- Przybyla, Laralynne;
- Chow, Eric
CRISPR genome editing approaches theoretically enable researchers to define the function of each human gene in specific cell types, but challenges remain to efficiently perform genetic perturbations in relevant models. In this work, we develop a library cloning protocol that increases sgRNA uniformity and greatly reduces bias in existing genome-wide libraries. We demonstrate that our libraries can achieve equivalent or better statistical power compared to previously reported screens using an order of magnitude fewer cells. This improved cloning protocol enables genome-scale CRISPR screens in technically challenging cell models and screen formats.