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使用深度突变扫描和碱基编辑对变异功能测量进行的并列比较。

A side-by-side comparison of variant function measurements using deep mutational scanning and base editing.

作者信息

Sokirniy Ivan, Inam Haider, Tomaszkiewicz Marta, Reynolds Joshua, McCandlish David, Pritchard Justin

机构信息

Huck Institute for the Life Sciences, University Park, PA 16802.

Department of Biomedical Engineering, University Park, PA 16802.

出版信息

bioRxiv. 2024 Sep 26:2024.06.30.601444. doi: 10.1101/2024.06.30.601444.

Abstract

Variant annotation is a crucial objective in mammalian functional genomics. Deep Mutational Scanning (DMS) 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 base editing measurements can annotate variant function and the extent of downstream experimental validation required. This study presents the first direct comparison of DMS and BE in the same lab and cell line. Results indicate that focusing on the most likely edits and highest efficiency sgRNAs enhances 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 the variants created in the pool, rather than sgRNA abundance, can recover high-quality variant annotation measurements in multiplexed pools. Taken together, our data show a surprising degree of correlation between base editor data and gold standard deep mutational scanning.

摘要

变异注释是哺乳动物功能基因组学的一个关键目标。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,关于高通量碱基编辑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。本研究首次在同一实验室和细胞系中对DMS和BE进行了直接比较。结果表明,关注最可能的编辑和最高效率的sgRNA可增强“金标准”DMS数据集与BE筛选之间的一致性。对在其窗口中进行单编辑的sgRNA进行简单筛选,就可以直接从大量文库的sgRNA测序中充分注释大部分变异。当不可避免地出现多编辑向导时,直接测量文库中产生的变异,而不是sgRNA丰度,可以在多重文库中恢复高质量的变异注释测量。综上所述,我们的数据显示碱基编辑器数据与金标准深度突变扫描之间存在惊人程度的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31f6/11455548/84d227300546/nihpp-2024.06.30.601444v2-f0001.jpg

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