Accurate classification of BRCA1 variants with saturation genome editing

By Gregory M. Findlay, R. Daza, Beth K. Martin, Melissa D. Zhang, Anh P. Leith, Molly Gasperini, Joseph D. Janizek, Xingfan Huang, Lea M. Starita, Jay Shendure. 2018

756 citations recorded by the source corpus.

Variants of uncertain significance fundamentally limit the clinical utility of genetic information. The challenge they pose is epitomized by BRCA1, a tumour suppressor gene in which germline loss-of-function variants predispose women to breast and ovarian cancer. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Here we use saturation genome editing to assay 96.5% of all possible single-nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Functional effects for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Over 400 non-functional missense SNVs are identified, as well as around 300 SNVs that disrupt expression. We predict that these results will be immediately useful for the clinical interpretation of BRCA1 variants, and that this approach can be extended to overcome the challenge of variants of uncertain significance in additional clinically actionable genes. Germline BRCA1 loss-of-function variants are associated with predisposition to early-onset breast and ovarian cancer; here the authors use CRISPR/Cas9 genome editing to functionally assess thousands of BRCA1 variants in order to facilitate the clinical interpretation of these variants.

Subfields: Genetics, Molecular Biology

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In Genetics

1. Joseph A. Marsh
2. B. Livesey

In Molecular Biology

1. Pushmeet Kohli
2. Joseph A. Marsh
3. B. Livesey
4. Alexander Pritzel

Citations in the corpus

• Using deep mutational scanning to benchmark variant effect predictors and identify disease mutations (2020, methodology): “For BRCA1, where there are DMS data sets based upon three different experimental phenotypes, the growth rate-based assay (Findlay et al , 2018) performs much better than those based upon yeast two-hybrid or E3 ubiquitin ligase activity (Starita et al , 2015).”
• Evaluating drug targets through human loss-of-function genetic variation (2019, neutral): “Such curation is essential prior to any recontact efforts, and establishing methods for high-throughput functional validation 48 of LoF variants is a priority.”
• Accurate proteome-wide missense variant effect prediction with AlphaMissense (2023, background): “…multiplexed assays of variant effect (MAVEs) systematically measure protein variant effects ( 4 ) and can accurately predict the clinical outcomes of variants ( 5 ), a proteome-wide survey of variant pathogenicity remains incomplete because of the cost and labor required for MAVE experiments ( 6 ).”