英国威康桑格研究所David J. Adams等研究人员合作发现，饱和基因组编辑可对RAD51C进行高分辨率功能映射。相关论文于2024年9月18日在线发表在《细胞》杂志上。
通过饱和基因组编辑（SGE），研究人员功能性地评估了9188种独特变异，包括超过99.5%的所有可能的编码序列单核苷酸变化。通过计算变异丰度的变化和高斯混合建模（GMM），研究人员将3094种变异功能性地分类为破坏性变异，并使用临床真实数据集揭示了变异分类的准确性/一致性超过99.9%。
细胞适应性是主要的检测指标，使研究人员观察到一种现象，即特定的错义变异表现出不同的耗竭动力学，可能表明它们代表低活性等位基因。
研究人员进一步探索了全面的功能图谱，揭示了RAD51C结构上的关键残基，并解决了在癌症家族中发现的变异。此外，通过对英国生物银行和大型多中心卵巢癌队列的调查，研究人员发现SGE耗竭的变异与癌症诊断之间存在显著关联。
据介绍，RAD51C中的致病变异会显著增加乳腺癌和卵巢癌的风险，而特定RAD51C等位基因的纯合个体可能发展为范可尼贫血。
附：英文原文
Title: High-resolution functional mapping of RAD51C by saturation genome editing
Author: Rebeca Olvera-León, Fang Zhang, Victoria Offord, Yajie Zhao, Hong Kee Tan, Prashant Gupta, Tuya Pal, Carla Daniela Robles-Espinoza, Fernanda G. Arriaga-González, Larissa Satiko Alcantara Sekimoto Matsuyama, Erwan Delage, Ed Dicks, Suzana Ezquina, Charlie F. Rowlands, Clare Turnbull, Paul Pharoah, John R.B. Perry, Maria Jasin, Andrew J. Waters, David J. Adams
Issue&Volume: 2024-09-18
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.
DOI: 10.1016/j.cell.2024.08.039
Source: https://www.cell.com/cell/abstract/S0092-8674(24)00968-1