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

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.

Multiplexed Functional Assessment of Genetic Variants in CARD11.

Genetic testing has increased the number of variants identified in disease genes, but the diagnostic utility is limited by lack of understanding variant function. CARD11 encodes an adaptor protein that expresses dominant-negative and gain-of-function variants associated with distinct immunodeficiencies. Here, we used a "cloning-free" saturation genome editing approach in a diploid cell line to simultaneously score 2,542 variants for decreased or increased function in the region of CARD11 associated with immunodeficiency. We also described an exon-skipping mechanism for CARD11 dominant-negative activity. The classification of reported clinical variants was sensitive (94.6%) and specific (88.9%), which rendered the data immediately useful for interpretation of seven coding and splicing variants implicated in immunodeficiency found in our clinic. This approach is generalizable for variant interpretation in many other clinically actionable genes, in any relevant cell type.

Reducing uncertainty in genetic testing with Saturation Genome Editing.

Accurate interpretation of human genetic data is critical for optimizing outcomes in the era of genomic medicine. Powerful methods for testing genetic variants for functional effects are allowing researchers to characterize thousands of variants across disease genes. Here, we review experimental tools enabling highly scalable assays of variants, focusing specifically on Saturation Genome Editing (SGE). We discuss examples of how this technique is being implemented for variant testing at scale and describe how SGE data for BRCA1 have been clinically validated and used to aid variant interpretation. The initial success at predicting variant pathogenicity with SGE has spurred efforts to expand this and related techniques to many more genes.

Clinical phenotypes combined with saturation genome editing identifying the pathogenicity of BRCA1 variants of uncertain significance in breast cancer.

Characterizing the pathogenicity of BRCA1 variants of uncertain significance (VUSs) is a major bottleneck in clinical management of BRCA1-associated breast cancer. Saturation genome editing (SGE) was recently reported as an innovative laboratory-based approach to assess the pathogenicity of BRCA1 variants. We combined clinical phenotypes and SGE score to identify the pathogenicity of BRCA1 VUSs detected in a cohort of 8,085 breast cancer patients. According to SGE function score, 33 out of 144 BRCA1 VUSs detected were classified into "loss of function" (n = 13), "intermediate" (n = 2), and "functional" (n = 18) groups. Compared with non-carriers, "loss of function" VUS carriers (n = 19) presented significantly worse clinicopathological characteristics. These included younger age at breast cancer diagnosis (44.4 years vs. 51.2 years, P = 0.01), stronger family history of any cancer (57.9% vs. 32.3%, P = 0.017) especially breast or ovarian cancer (47.4% vs. 9.3%, P < 0.001), more bilateral breast cancer (31.6% vs. 3.4%, P < 0.001), and triple-negative breast cancer (47.4% vs. 12.8%, P < 0.001), which were comparable to those of pathogenic variant carriers. In contrast, the clinical phenotypes of "functional" VUS carriers were similar to those of non-carriers. These results indicated that SGE was a reliable method in BRCA1 variant classification. Combining SGE function score and the available evidence, twelve out of 33 BRCA1 VUSs were reclassified as pathogenic or likely pathogenic variants and one was benign.