Dataset Information

Saturation genome Editing of BRCA2 variants from C-terminal DNA binding domain

ABSTRACT: Accurate interpretation of genetic variation is a critical step towards realizing the potential of precision medicine. Sequencing-based genetic tests have uncovered a vast array ofBRCA2sequence variants. Due to limited clinical, familial and/or epidemiological data, thousands of variants are considered to be variants of uncertain significance (VUS). Here we have utilized CRISPR-Cas9-based saturation genome editing (SGE) in a humanized-mouse embryonic stem cell line. We have categorized nearly all possible missense single nucleotide variants (SNVs) encompassing the C-terminal DNA binding domain ofBRCA2.We have generated the function scores for 6270 SNVs, covering 95.5% of possible SNVs in exons 15-26 spanning residues 2479-3216, including 1069 unique missense VUS, with 81% functional and 14% found to be nonfunctional. Our classification aligns strongly with pathogenicity data from ClinVar, orthogonal functional assays and computational meta predictors. Our statistical classifier exhibits 92.2% sensitivity and 96% specificity in distinguishing clinically benign and pathogenic variants recorded in ClinVar. Furthermore, we offer proactive evidence for 617 SNVs being non-functional and 3396 SNVs being functional demonstrated by impact on cell growth and response to DNA-damaging drugs like cisplatin and olaparib. This classification serves as a valuable resource for interpreting unidentified variants in the population and for physicians and genetic counselors assessingBRCA2VUSs in patients.

ORGANISM(S): Mus musculus

PROVIDER: GSE248438 | GEO | 2024/09/27

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Germline BRCA2 loss-of function (LOF) variants identified by clinical genetic testing predispose to breast, ovarian, prostate and pancreatic cancer. However, variants of uncertain significance (VUS) (n>5000) limit the clinical use of testing results. Thus, there is an urgent need for functional characterization and clinical classification of all BRCA2 variants. Here we report on comprehensive saturation genome editing-based functional characterization of 99% of all possible single nucleotide variants (SNVs) in the BRCA2 DNA Binding Domain hotspot for pathogenic missense variants that is encoded by exons 15 to 26. The assay was based on deep sequence analysis of HAP1 haploid cells endogenously targeted using a CRISPR/cas9 knockin approach. A total of 6959 SNVs were characterized for effects on cell survival. The assay was validated relative to nonsense and synonymous variants, ClinVar pathogenic/likely pathogenic and benign/likely benign variants and homology directed repair cell based DNA repair assay results, all of which showed >94% sensitivity and specificity. Variants were assigned posterior probabilities of pathogenicity using a VarCall two component Bayesian mixture model and were further grouped according to ACMG strength of evidence under the PS3/BS3 rule resulting in Benign Strong (n=5430), Benign Moderate (n=190), Benign Supporting (n=61), VUS (122), Pathogenic Strong (n=1021), Pathogenic Moderate (n=88), and Pathogenic Supporting (n=47). Breast cancer case-control association studies showed that pooled SNVs encoding functionally pathogenic missense variants were associated with increased risks of breast (odds ratio (OR)3.81, 95%CI: 2.88-5.07) and ovarian cancer (OR 5.93, 95%CI: 4.12-8.52). The functional data were also combined with other sources of information in the ClinGen BRCA1/2 VCEP ACMG/AMP-classification model. A total of 785 SNVs, including 261 missense SNVs, were classified as pathogenic or likely pathogenic, while 5566 SNVs, including 3786 missense SNVs, were classified as benign or likely benign. These classified variants can now be used for risk assessment and clinical care of variant carriers.

Dataset Information

Saturation genome Editing of BRCA2 variants from C-terminal DNA binding domain

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets