Laboratory for Genomics Research, San Francisco, CA, 94158, USA.
Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA.
Genome Biol. 2024 Jan 19;25(1):25. doi: 10.1186/s13059-023-03132-3.
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.
CRISPR 基因组编辑方法从理论上使研究人员能够在特定细胞类型中定义每个人类基因的功能,但在相关模型中有效地进行遗传干扰仍然存在挑战。在这项工作中,我们开发了一种文库克隆方案,该方案提高了 sgRNA 的均匀性,并大大降低了现有全基因组文库中的偏倚。我们证明,与以前使用数量级更少的细胞报告的筛选相比,我们的文库可以实现等效或更好的统计功效。这种改进的克隆方案使技术上具有挑战性的细胞模型和筛选格式能够进行基因组规模的 CRISPR 筛选。
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