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RAD51C 的高分辨率功能图谱通过饱和基因组编辑。

High-resolution functional mapping of RAD51C by saturation genome editing.

机构信息

Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK; Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Querétaro, Mexico.

Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Developmental Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

出版信息

Cell. 2024 Oct 3;187(20):5719-5734.e19. doi: 10.1016/j.cell.2024.08.039. Epub 2024 Sep 18.

Abstract

Pathogenic variants in RAD51C confer an elevated risk of breast and ovarian cancer, while individuals homozygous for specific RAD51C alleles may develop Fanconi anemia. Using saturation genome editing (SGE), we functionally assess 9,188 unique variants, including >99.5% of all possible coding sequence single-nucleotide alterations. By computing changes in variant abundance and Gaussian mixture modeling (GMM), we functionally classify 3,094 variants to be disruptive and use clinical truth sets to reveal an accuracy/concordance of variant classification >99.9%. Cell fitness was the primary assay readout allowing us to observe a phenomenon where specific missense variants exhibit distinct depletion kinetics potentially suggesting that they represent hypomorphic alleles. We further explored our exhaustive functional map, revealing critical residues on the RAD51C structure and resolving variants found in cancer-segregating kindred. Furthermore, through interrogation of UK Biobank and a large multi-center ovarian cancer cohort, we find significant associations between SGE-depleted variants and cancer diagnoses.

摘要

RAD51C 中的致病变异会增加乳腺癌和卵巢癌的风险,而纯合特定 RAD51C 等位基因的个体可能会发展成范可尼贫血。我们使用饱和基因组编辑(SGE),对 9188 个独特的变体进行了功能评估,包括 >99.5%的所有可能的编码序列单核苷酸改变。通过计算变体丰度的变化和高斯混合建模(GMM),我们将 3094 个变体功能分类为破坏性,并使用临床真实数据集揭示变体分类的准确性/一致性>99.9%。细胞适应性是主要的检测结果,使我们能够观察到特定错义变体表现出不同的耗竭动力学的现象,这可能表明它们代表了功能不全的等位基因。我们进一步探索了我们详尽的功能图谱,揭示了 RAD51C 结构上的关键残基,并解决了在癌症分离家族中发现的变体。此外,通过对英国生物库和一个大型多中心卵巢癌队列的研究,我们发现 SGE 耗竭变体与癌症诊断之间存在显著关联。

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