Sokirniy Ivan, Inam Haider, Tomaszkiewicz Marta, Reynolds Joshua, McCandlish David, Pritchard Justin
Huck Institute for the Life Sciences, University Park, PA 16802, United States.
Department of Biomedical Engineering, University Park, PA 16802, United States.
Nucleic Acids Res. 2025 Jul 19;53(14). doi: 10.1093/nar/gkaf738.
Variant annotation is a crucial objective in mammalian functional genomics. Deep mutational scanning (DMS) using saturation libraries of complementary DNAs (cDNAs) is a well-established method for annotating human gene variants, but CRISPR base editing (BE) is emerging as an alternative. However, questions remain about how well high-throughput BE measurements can annotate variant function and the extent of downstream experimental validation required. This study is the first direct comparison of cDNA DMS and BE in the same lab and cell line. We focus on how well short guide RNA (sgRNA) depletion or enrichment is explained by the predicted edits within the editing "window" defined by the sgRNA. The most likely predicted edits enhance the agreement between a "gold standard" DMS dataset and a BE screen. A simple filter for sgRNAs making single edits in their window could sufficiently annotate a large proportion of variants directly from sgRNA sequencing of large pools. When multi-edit guides are unavoidable, directly measuring edits in medium-sized validation pools can recover high-quality variant annotation data. Our data show a surprisingly high degree of correlation between base editor data and gold standard DMS. We suggest that the main variable measured in base editor screens is the desired base edits.
变异注释是哺乳动物功能基因组学中的一个关键目标。使用互补DNA（cDNA）饱和文库进行深度突变扫描（DMS）是一种成熟的注释人类基因变异的方法，但CRISPR碱基编辑（BE）正在成为一种替代方法。然而，关于高通量BE测量在注释变异功能方面的效果以及所需下游实验验证的程度，仍然存在问题。本研究是在同一实验室和细胞系中对cDNA DMS和BE进行的首次直接比较。我们关注的是，在由sgRNA定义的编辑“窗口”内，预测编辑对短引导RNA（sgRNA）的缺失或富集的解释程度。最有可能的预测编辑增强了“金标准”DMS数据集与BE筛选之间的一致性。对在其窗口内进行单编辑的sgRNA进行简单过滤，就可以直接从大池的sgRNA测序中充分注释很大一部分变异。当不可避免地出现多编辑引导时，直接在中等规模的验证池中测量编辑可以恢复高质量的变异注释数据。我们的数据显示，碱基编辑器数据与金标准DMS之间存在惊人的高度相关性。我们认为，在碱基编辑器筛选中测量的主要变量是所需的碱基编辑。
