Tumor genomes often harbor a complex spectrum of single nucleotide alterations and chromosomal rearrangements that can perturb protein function. Prime editing has been applied to install and evaluate genetic variants, but previous approaches have been limited by the variable efficiency of prime editing guide RNAs. Here we present a high-throughput prime editing sensor strategy that couples prime editing guide RNAs with synthetic versions of their cognate target sites to quantitatively assess the functional impact of endogenous genetic variants. We screen over 1,000 endogenous cancer-associated variants of TP53—the most frequently mutated gene in cancer—to identify alleles that impact p53 function in mechanistically diverse ways. We find that certain endogenous TP53 variants, particularly those in the p53 oligomerization domain, display opposite phenotypes in exogenous overexpression systems. Our results emphasize the physiological importance of gene dosage in shaping native protein stoichiometry and protein–protein interactions, and establish a framework for studying genetic variants in their endogenous sequence context at scale.

肿瘤基因组通常包含一系列复杂的单核苷酸改变和染色体重排，可能会扰乱蛋白质功能。Prime 编辑已被应用于安装和评估遗传变异，但以前的方法受到 Prime 编辑引导 RNA 的可变效率的限制。在这里，我们提出了一种高通量prime编辑传感器策略，将prime编辑引导RNA与其同源靶位点的合成版本结合起来，以定量评估内源遗传变异的功能影响。我们筛选了超过 1,000 种与癌症相关的TP53内源性变体（癌症中最常见的突变基因），以识别以不同机制影响 p53 功能的等位基因。我们发现某些内源性TP53变体，特别是 p53 寡聚化结构域中的变体，在外源过表达系统中表现出相反的表型。我们的结果强调了基因剂量在塑造天然蛋白质化学计量和蛋白质-蛋白质相互作用方面的生理重要性，并建立了一个框架来大规模研究内源序列背景下的遗传变异。