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High-resolution functional mapping of RAD51C by saturation genome editing
Rebeca Olvera-León1, Fang Zhang2, Victoria Offord3
1Wellcome 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.
Cell
|September 19, 2024
Summary
Pathogenic variants in RAD51C increase breast and ovarian cancer risk. Saturation genome editing (SGE) functionally assessed thousands of variants, identifying disruptive mutations and their links to cancer diagnoses.
Area of Science:
- Genetics and genomics
- Molecular biology
- Cancer research
Background:
- Pathogenic variants in RAD51C are associated with increased risks of breast and ovarian cancers.
- Specific RAD51C alleles can lead to Fanconi anemia when present in homozygous individuals.
Purpose of the Study:
- To functionally assess a comprehensive set of variants in the RAD51C gene.
- To identify disruptive RAD51C variants and their clinical significance.
- To explore the functional impact of RAD51C variants on cancer risk.
Main Methods:
- Saturation genome editing (SGE) was employed to functionally assess 9,188 unique RAD51C variants, covering >99.5% of all possible coding sequence single-nucleotide alterations.
- Variant abundance changes and Gaussian mixture modeling (GMM) were used for functional classification of variants.
- Cell fitness assays served as the primary readout, with analysis of depletion kinetics to identify potential hypomorphic alleles.
- Clinical truth sets were utilized to validate variant classification accuracy.
Main Results:
- Over 3,094 RAD51C variants were functionally classified as disruptive.
- Variant classification achieved an accuracy/concordance rate exceeding 99.9% when compared to clinical truth sets.
- Distinct depletion kinetics were observed for specific missense variants, suggesting they may be hypomorphic alleles.
- An exhaustive functional map of RAD51C variants was generated, highlighting critical residues and resolving variants from cancer-segregating families.
- Significant associations were found between SGE-depleted variants and cancer diagnoses in UK Biobank and a large ovarian cancer cohort.
Conclusions:
- Saturation genome editing provides a highly accurate and comprehensive method for functional variant classification in RAD51C.
- The study identified numerous disruptive RAD51C variants and potential hypomorphic alleles, enhancing our understanding of their roles in cancer predisposition.
- The findings link specific RAD51C variant classifications to increased cancer risk, offering valuable insights for clinical diagnostics and genetic counseling.
