Function verification method of BRCA1 / 2 gene meaning unclear variation

Abstract

The invention discloses a functional verification method of BRCA1 / 2 gene meaning unclear variation. By introducing only one target variation in each experiment and combining with optimized gRNA and template design, the method ensures that the target variation has high initial abundance in an edited cell population, so that background noise of next-generation sequencing detection and phenotype analysis is remarkably reduced, and sensitivity and reliability of variation function signal detection are improved. According to the method, a function verification scheme which is more flexible, accurate and easy to operate is provided for interpretation of the BRCA1 / 2 meaning unclear variation, and the bottleneck that the meaning unclear variation function data is difficult to acquire and interpret is hopefully solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of biotechnology, and particularly relates to a method for verifying the function of a variant of uncertain significance. BRCA1 / 2 BACKGROUND

[0002] BRCA1 / 2 Gene refers to BRCA1 gene or BRCA2 gene, BRCA1 the gene is breast cancer gene 1, BRCA2 the gene is breast cancer gene 2. BRCA1 / 2 are two genes that inhibit the occurrence of malignant tumors, and play an important role in regulating the replication of human cells, the repair of damaged DNA, and the normal growth of cells. Families with mutations in this gene tend to have a high incidence of breast cancer, usually occurring at a younger age, and have a higher risk of contralateral breast cancer and ovarian cancer.

[0003] BRCA1 / 2 Gene detection has been widely used in clinical practice. However, the variant of uncertain significance (VUS) in it brings significant difficulties to patient consultation, clinical decision-making and medical resource allocation due to its uncertainty in clinical significance. The detection rate of variants of uncertain significance in Asian population BRCA1 / 2 up to 47.8% (Kurian A W, Ward K C, Abrahamse P, et al. Time Trends in Receipt of Germline Genetic Testing and Results for Women Diagnosed With Breast Cancer or Ovarian Cancer, 2012-2019 [J]. J Clin Oncol , 2021, 39(15): 1631-1640.), and the existing functional data far cannot meet the clinical needs.

[0004] ​Traditional unknown significance variant functional verification methods are often only suitable for specific functional domains or specific types of variant evaluation, and are difficult to meet the high-throughput demand. Based on CRISPR-Cas9 gene editing technology, testable variants can be introduced into disease genes while retaining the natural genomic background, thereby improving the accuracy of functional research by maintaining endogenous cell transcription and splicing mechanisms, greatly simplifying and accelerating the process of site-directed mutagenesis. However, using CRISPR-based editing technology to generate stable cell lines carrying specific target variants is still a time-consuming and laborious process, usually requiring more than a month to screen single clones. Saturation genome editing (SGE) can achieve multi-site parallel analysis and high-throughput evaluation of variants, but has three shortcomings: 1. Complex saturation mutation libraries need to be synthesized, and cells need to be enriched by fluorescence-activated cell sorting and other technologies, which is complex and costly; 2. The frequency of each variant in the cell pool is low, and the background noise of second-generation sequencing is large, affecting the accuracy of the results; 3. The implementation of high-throughput evaluation relies on continuous genomic region targeting (about 100-150bp), while in reality, unknown significance variants are often scattered on the gene, so if the SGE method is used for functional verification after sequencing the unknown significance variant results, it cannot take advantage of its high-throughput, and may even waste resources ([1]Sahu S, Galloux M, Southon E, et al. Saturation genome editing-based clinical classification of BRCA2 variants[J]. Nature ,2025,638(8050):538-545. [2]Huang H, Hu C, Na J, et al. Functional evaluation and clinical classification of BRCA2 variants[J]. Nature , 2025,638(8050):528-537. [3]Findlay G M, Daza R M, Martin B, et al. Accurate classification of BRCA1 variants with saturation genome editing[J]. Nature , 2018,562(7726):217-222.). SUMMARY

[0005] The present application provides aBRCA1 / 2 Method for verifying function of gene variant with unknown significance. Overcome the problems of low flux, high cost and incomplete coverage of function verification of scattered variants with unknown significance in BRCA1 / 2 gene in the prior art, flexible and accurate, suitable for clinical laboratory.

[0006] A method for verifying function of gene variant with unknown significance BRCA1 / 2 The method for verifying function of gene variant with unknown significance comprises the following steps: S1, for each to-be-tested variant with unknown significance, designing one gRNA and two HDR templates for single-point editing, one of the two HDR templates containing a variant with unknown significance sequence and the other containing a control variant sequence; S2, for each to-be-tested variant with unknown significance or control variant, respectively, co-transferring the gRNA, HDR template and Cas9 enzyme into a haploid host cell for gene editing; S3, dynamic abundance detection, detecting the abundance of cells carrying the to-be-tested variant with unknown significance after culturing the gene-edited cells; S4, performing function scoring of the variant with unknown significance according to the dynamic abundance detection result.

[0007] Preferably, the haploid host cell is a haploid HAP1 cell. More preferably, in the haploid HAP1 cell, LIG4 gene knockout.

[0008] Preferably, the control variant selects a synonymous mutation as close as possible to the to-be-tested variant with unknown significance. More preferably, the control variant selects a known benign or possibly benign variant within ±3bp of the to-be-tested variant with unknown significance.

[0009] Preferably, the gRNA selects a gRNA with a cutting site within 10nt of the to-be-tested variant with unknown significance, a higher target efficiency score and a lower off-target risk.

[0010] Preferably, 0-3 blocking mutations are introduced in the HDR template near the PAM site or the 3' end adjacent region of the gRNA, all the blocking mutations are confirmed as benign or possibly benign variants; the non-complementary strand of the gRNA is selected as the HDR template strand; for missense variants, splice site variants, <6bp small fragment insertion or deletion variants, the length of the HDR template is designed to be 80-100nt; the two HDR templates used for the same variant with unknown significance have the same length and contain the same blocking mutations.

[0011] Preferably, before function verification, low pathogenicity variants with unknown significance are filtered using a variety of computer prediction tools to reduce verification targets, wherein only missense variants, splice site variants, small fragment insertion or deletion variants with a length of ≤6bp that are predicted as harmful, pathogenic or affecting function by at least one computer prediction tool are included in further function verification tests.

[0012] Preferably, in step S3, the gene-edited cells are cultured for 3-5 days, and part of the cells are collected for gene sequencing. The remaining cells are cultured for at least 2 passages, and then collected for gene sequencing. The sequence data are counted, and the sequences carrying the target variation and the blocking mutation, or only carrying the target variation, are counted, i.e., the abundance of cells carrying the variation of unknown significance.

[0013] The purpose of the first sampling is to preliminarily evaluate the proportion of edited cells in the population of gene-edited cells. According to the instructions of the gene editing reagent supplier, the detection can be carried out at 48-72 hours after transfection, at which time the editing effect has tended to be stable. However, in actual operation, if the sample is collected at 3 days after transfection, part of the samples are difficult to support subsequent experiments due to insufficient cell quantity. Therefore, in combination with the instructions of the reagent and the actual feasibility, we determine the first sampling time as 3-5 days after transfection, and preferably, the fourth day can be selected as a representative time point, which can ensure that the editing effect is fully manifested while ensuring sufficient cell quantity.

[0014] The purpose of the second sampling is to analyze the change of the proportion of edited cells with time, and then to evaluate the functional difference of different genotypes under the condition of competitive growth. In theory, prolonging the culture time helps to more accurately reflect the composition change of the cell population in the stable state, but also increases the experimental period and cost. If the interval between the two samplings is too short, it may be difficult to effectively distinguish the functional effects of different variations due to insignificant change of cell proportion. Based on the actual operation experience, we find that an interval of 2-3 passages (about 4-6 days) between the first and second samplings can achieve a good discrimination effect. Therefore, we determine the second sampling time as 4-6 days after the first sampling, and preferably, the tenth day can be selected as an example in this application.

[0015] The gene sequencing preferably uses second-generation sequencing.

[0016] More preferably, in step S4, the calculation formula of the functional score S of the function of the variation of unknown significance is: S=(A vus, Dy ×A Control, Dx ) / (A vus, Dx ×A Control, Dy ), wherein A vus, Dx is the abundance of cells carrying the variation of unknown significance detected by the first gene sequencing, A vus, Dy is the abundance of cells carrying the variation of unknown significance detected by the second gene sequencing, A Control, Dx is the abundance of cells carrying the control variation detected by the first gene sequencing, and A Control, Dy is the abundance of cells carrying the control variation detected by the second gene sequencing. A low functional score S reflects that the variation of unknown significance leads to BRCA1 / 2 loss of gene function.

[0017] In the case of the first sampling at day 4 and the second sampling at day 10, the formula for calculating the functional score S of the significance-unknown variant function score in step S4 is: S = (A vus, D10 × A Control, D4 ) / (A vus, D4 × A Control, D10 ), wherein A vus, D4 is the cell abundance carrying the to-be-tested significance-unknown variant at day 4, A vus, D10 is the cell abundance carrying the to-be-tested significance-unknown variant at day 10, A Control, D4 is the cell abundance carrying the control variant at day 4, and A Control, D10 is the cell abundance carrying the control variant at day 10. A low functional score S indicates that the to-be-tested significance-unknown variant causes BRCA1 / 2 loss of gene function. A functional score S < 0.5 is considered to be a loss-of-function variant.

[0018] Since we found that this method has good discrimination when verified according to variants of known clinical classification, the functional score of benign / possibly benign is close to 1 or greater than 1, and the pathogenic / possibly pathogenic variant is much less than 1, therefore, we define S ≥ 0.5 as a functional variant, and S < 0.5 as a loss-of-function variant.

[0019] Compared with the prior art, the present application has the following beneficial effects: This method allows precise introduction of a single target variant, including single nucleotide variants and small insertion / deletion variants, at any selected genomic location, and can be customized for functional verification of clinically detected significance-unknown variants.

[0020] By introducing only one variant in each experiment and combining optimized gRNA and template design, our method ensures that the target variant has a high initial abundance in the edited cell population, thereby significantly reducing the background noise of second-generation sequencing detection and phenotype analysis, and improving the sensitivity and reliability of functional signal detection.

[0021] Since each experiment targets a single variant, this method simplifies the experimental process, eliminating the complex steps of saturated mutation library construction and cell enrichment. Compared with the SGE method, it significantly reduces the demand for synthesis, sequencing and computing resources, and has lower requirements for experimental equipment, data processing capacity and personnel professional skills, making it easier to implement and promote in conventional clinical research laboratories or institutions with basic molecular biology capabilities.

[0022] This method provides a more flexible, accurate and easy-to-operate functional verification scheme for interpretation of BRCA1 / 2 significance-unknown variants, and is expected to solve the difficult bottleneck of obtaining and interpreting functional data of significance-unknown variants. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 Figure 1 shows the flow chart of the present functional verification method.

[0024] Figure 2 Figure 2 shows the ploidy analysis results in Example 1, wherein, Figure 2 A in Figure 2 is haploid cells; Figure 2 B in Figure 2 is a mixture of haploid cells and diploid cells; Figure 2 C in Figure 2 is diploid cells.

[0025] Figure 3 Figure 3 shows the HAP1 cell line in Example 1. LIG4 Gene knockout results.

[0026] Figure 4 Figure 4 shows the cell abundance carrying known classification variants on day 4 and day 10 in Example 2. In which, each mutation is detected on day 4 (D4) and day 10 (D10), and the variants are displayed according to known pathogenicity (benign / possibly benign, pathogenic / possibly pathogenic variants), and the filling pattern and filling color of each column represent time and classification, respectively. In some cases, the cell abundance is very low, and the column height is not obvious in the figure.

[0027] Figure 5 Figure 5 shows the functional score difference of known classification variants in Example 2.

[0028] Figure 6 Figure 6 shows the identification process of variants of unknown significance in Example 3.

[0029] Figure 7 Figure 7 shows the functional score of variants of unknown significance in Example 3.

[0030] Figure 8 Figure 8 shows the comparison of functional verification results of variants of unknown significance in Example 3 with the results of existing large-scale functional verification experiments. DETAILED DESCRIPTION

[0031] Example 1: HAP1- LIG4 Knockout (KO) cell line construction and verification Since the present functional verification method relies on haploid HAP1 cell lines (human chronic myeloid leukemia cells). Haploid cells only contain one set of chromosomes, which can avoid the masking of the functional effect of mutations in heterozygous state, and are an ideal model for functional research. Previous studies have confirmed that BRCA1 / 2 genes are essential for the survival of haploid cells, and the loss of function of either gene can lead to cell death (Blomen V A, Majek P, Jae L T, et al. Gene essentiality and synthetic lethality in haploid human cells[J].Science , 2015, 350(6264): 1092-1096.). In addition, inhibition of the key molecule DNA ligase IV (encoded by LIG4 gene) of the non-homologous end joining (NHEJ) pathway can significantly improve the efficiency of precise editing mediated by homology-directed repair (HDR) in mammalian cells CRISPR editing (Chu V T, Weber T, Wefers B, et al. Increasing the efficiency of homology-directed repair for CRISPR-Cas9-induced precise gene editing in mammalian cells [J]. Nat Biotechnol , 2015, 33(5): 543-548.). Therefore, to improve the efficiency of mutation introduction, we first constructed a LIG4 gene knockout monoclonal haploid HAP1 cell line (HAP1- LIG4 KO) using CRISPR technology.

[0032] To enrich haploid HAP1 cells, cells at 60%-70% confluence in T75 culture bottles were digested. The cell suspension after digestion was resuspended with complete medium containing 7 μg / mL Hoechst 34580 (Selleck) and incubated at 37°C in the dark for 45 minutes. After incubation, the cells were collected by centrifugation and resuspended with phosphate buffered saline containing 1% fetal bovine serum, Hoechst 34580 and propidium iodide (MedChemExpress). MoFlo Astrios EQ (Beckman) flow cytometer was used for haploid cell sorting, and the sample pressure was set to 1-4 (speed 1000-1500 per second), and the excitation light source was 405 nm and 561 nm laser. The sorting strategy was: excluding propidium iodide positive (dead cell) signal, selecting the cell population with relatively low Hoechst 34580 fluorescence intensity (haploid peak) in the two main cell populations under 405 nm excitation light. The sorted haploid cells were collected in complete medium, and inoculated into culture dishes of appropriate size according to cell counting.

[0033] A specific gRNA sequence (5'-GCATAATGTCACTACAGATC-3') was designed, and a single-stranded DNA oligonucleotide was synthesized, annealed to form a double-stranded fragment, and then ligated into a linearized CRISPR / Cas9 vector (Genechem) containing a ZsGreen green fluorescent protein and a puromycin resistance gene by enzyme digestion. The ligation product was transformed into E. coli Stbl3 competent cells, and positive clones were screened by colony PCR and verified by bidirectional sequencing to construct a CRISPR / Cas9 plasmid targeting the LIG4 gene. Endotoxin-free (<0.005 EU / μg) plasmids were extracted for subsequent experiments.

[0034] Well-grown HAP1 cells (Horizon) were seeded in a T25 culture flask, and when the confluence reached 50%-60% (about 16-20 hours), transfection was performed. Lipofectamine 3000 (Thermo Fisher Scientific) transfection reagent was used: 5 μL of the reagent was diluted in 250 μL of Opti-MEM; another 5 μg of plasmid DNA was diluted in 250 μL of Opti-MEM, and 10 μL of P3000 Enhancer was added, and mixed well. The above two solutions were mixed in equal amounts, and incubated at room temperature for 10-15 minutes, then 500 μL of the complex was added to the cell culture system. After 48 hours of transfection, the medium was replaced with fresh medium, and the expression of ZsGreen was observed under an inverted fluorescence microscope under 488 nm blue light excitation. About 24 hours after transfection, single ZsGreen-positive cells were sorted into a 96-well plate containing complete medium using flow cytometric sorting technology. After 1-2 weeks of monoclonal cell culture, green fluorescent positive monoclonal cells were selected for further culture for 1-2 weeks, and the ploidy and knockout efficiency were identified.

[0035] The Attune NxT (Thermo Fisher) flow cytometer was used to analyze the ploidy of the cells. The cells to be tested were collected, stained with iodinated propidium, and then detected on the machine. The upper limit of acquisition was set to 20,000 cells, and the flow rate was 12.5 cells / s. Since haploid HAP1 cells can spontaneously transform from haploid to diploid, wild-type HAP1 cells that have been subcultured for more than 30 generations were used as controls (C in Figure 2 ). By analyzing the scatter plot of cell number and iodinated propidium fluorescence intensity, the haploid cell peak (G0 / G1 phase and G2 / M phase) was determined by comparing the control cells. The haploid cell line should have only two main peaks (corresponding to the G0 / G1 phase and the G2 / M phase of the cell cycle, respectively), and the fluorescence intensity of the two main peaks should be 1 / 2 of the two main peaks of the corresponding high-generation cell line (A in Figure 2 ). Cells containing both haploid and diploid cells show three cell peaks (B in Figure 2(B) The FlowJo software was used to analyze and visualize the ploidy analysis experimental data.

[0036] Genomic DNA was extracted from haploid cell clones using the EZNA Tissue DNA Extraction Kit (Omega Bio-tek). Specific PCR primers (approximately ±600 bp flanking the editing site) were designed (forward primer: 5'-TTTTGCAGATTTGTGTTCAACTTTAGAACG-3'; reverse primer: 5'-TTGTTTTACCATAATTCCCTCTTCTCTTTT-3'). The PCR products were amplified and Sanger sequenced to validate the results in HAP1 cells. LIG4 The effect of gene knockout. The results showed that... LIG4 A 26bp frameshift deletion mutation was generated in the gene, suggesting... LIG4 Gene knockout successful ( Figure 3 ).

[0037] Example 2: Validation of Known Clinical Classification Variations To verify the effectiveness of this method, we selected 11 known taxonomic variants (data from the ClinVar database, accessed on August 7, 2023) reviewed by an expert panel accredited by the Clinical Genome Resource Center (ClinGen) for testing: 5 BRCA1 Variants (2 benign / probably benign variants: c.3418A>G, c.1233T>G; 3 pathogenic / probably pathogenic variants: c.390C>A, c.5089T>C, c.5513T>A) and 6 BRCA2 Variants (3 benign / probably benign variants: c.5552T>G, c.8182G>A, c.2803G>A; 3 pathogenic / probably pathogenic variants: c.8486A>G, ​​c.5966C>G, c.5946del). Testing methods are as follows: Figure 1 As shown.

[0038] Based on the aforementioned design principles, we used the Alt-R™ HDR design tool (Integrated DNA Technologies) to assist in the design of gRNA and HDR template oligonucleotides, summarized in Table 1. The crRNA was synthesized by Integrated DNA Technologies, and the HDR template oligonucleotides were synthesized by Sangon Biotech (Shanghai) Co., Ltd.

[0039] Table 1. crRNAs and HDR template oligonucleotides used for validation of known clinical classification variants (VUS template and control template in the table).

[0040] 200 μΜ crRNA was mixed with equal volume of 200 μΜ tracrRNA (Integrated DNA Technologies) to a final concentration of 100 μΜ each. The mixture was heated at 95 °C for 5 min and then cooled to room temperature to form gRNA. Then 62 μΜ Cas9 enzyme (Integrated DNA Technologies) was added and incubated at room temperature for 20 min to form Ribonucleoprotein (RNP) complex.

[0041] HAP1- LIG4 KO cells were seeded at a higher density 16-20 hours before nucleofection. Cells were harvested by digestion, counted and adjusted to 2 x 10 5 cells, washed once with 1 x phosphate buffered saline and centrifuged to remove the supernatant. Cells were resuspended in 20 μΐ, SE nucleofection reagent (Lonza) and pre-assembled RNP complex, 100 pmol HDR template oligo and 100 pmol electroporation enhancer (Integrated DNA Technologies) were added. Nucleofection was performed using 4D-Nucleofector™ system (Lonza) with program EO-100. Immediately after nucleofection, cells were transferred to a 96-well plate containing 150 μΐ, pre-warmed culture medium and incubated in the incubator.

[0042] Cells were cultured to day 4, and about 3 / 4 of each sample was harvested; the remaining 1 / 4 of cells were cultured to day 10 and then harvested. Genomic DNA was extracted using E.Z.N.A.® Tissue DNA Kit (Omega Bio-tek). For each target variant, PCR primers were designed to amplify a 200-280 bp fragment, ensuring that the target variant was not located within the first 20 bp of the amplified product. PCR amplification was performed using high-fidelity KAPA HiFi HotStart ReadyMix (Roche). The quality of the PCR products was detected by agarose gel electrophoresis. The DNA concentration was accurately quantified using Qubit, and samples with a concentration of ≥0.5 μg were used for library construction. The DNA samples were subjected to end repair, A-tailing, ligation of sequencing adapters to both ends, and purification (without intermediate PCR amplification) to construct a PCR-free library. After passing the quality control, the library was sequenced on the Illumina platform in a double-end 150 bp (PE150) mode according to the effective concentration. Samples with a quality index Q30 ≥ 80% were selected for subsequent analysis. The R1 and R2 sequencing reads were spliced using FLASH software. The spliced sequences were aligned to the reference sequence using BLAST software, and multiple sequence alignment was performed using MAFFT software. All sequence data were counted, and sequences carrying target variants and blocking mutations, or only carrying target variants, were counted separately.

[0043] The results showed that the cell abundance at day 4 was not directly related to whether the variant was pathogenic / possibly pathogenic ( Figure 4 ), which was related to the difference in CRISPR editing efficiency of variants at different positions of the gene. Therefore, the abundance at a single time point cannot directly determine the functional impact of the variant. Compared with day 4, the relative abundance of cells carrying pathogenic / possibly pathogenic variants at day 10 decreased significantly; while the abundance of cells carrying benign / possibly benign variants changed little or increased slightly ( Figure 4 ). This phenomenon was due to the fact that cells carrying pathogenic / possibly pathogenic variants (loss of function) were at a disadvantage in competitive growth under population selection pressure, while benign / possibly benign variants (normal function) did not affect cell fitness. By comparing the abundance changes of cells carrying the test variant and control variant, the functional score of each variant was calculated according to the following formula: S = (A vus, D10 × A Control, D4 ) / (A vus, D4 × A Control, D10 ).

[0044] The results showed that the functional score of benign / possibly benign variants was approximately equal to or greater than 1, while the functional score of pathogenic / possibly pathogenic variants was much less than 1 ( Figure 5 , Wilcoxon rank-sum test P=0.004329, effect size δ=-1), indicating that the method can effectively distinguish between pathogenic / potentially pathogenic and benign / potentially benign variants.

[0045] Example 3: Application of computer-based pre-screening to breast cancer patients BRCA1 / 2 Interpretation and Verification of Variations with Unclear Significance In Example 3, we applied this method to 63 breast cancer patients identified in a real-world population. BRCA1 / 2 Interpretation of variants of unknown significance. We first used ten different computer prediction tools to exclude some variants of unknown significance with low pathogenicity. Seven tools (AlphaMissense, REVEL, EVE, gMVP, MetaRNN, DeepSAV, and MutScore) were used for missense variant prediction, and three tools (dbscSNV, MaxEntScan, and SpliceAI) were used for splice site variant prediction. Most of the selected tools are based on machine learning algorithms, while the rest are ensemble methods or classic methods widely used in clinical practice. The prediction results are summarized in Table 2. In short, 28 (44.4%) variants were identified. BRCA1 / 2 Variations of unknown significance were considered to have an extremely low probability of being pathogenic or possibly pathogenic and were excluded from functional validation.

[0046] Table 2. Computer prediction results for variants of unknown significance.

[0047] * P: pathogenic, VUS: variant of uncertain significance, B: benign; ** D: deleterious, T: tolerable; *** A: affected, U: unaffected; ****Missense / splicing site variants that meet the following criteria are defined as pred_P: predicted as "deleterious (D)", "pathogenic (P)" or "affected (A)" by at least one algorithmic tool; missense / splicing site variants that are not predicted as "deleterious (D)", "pathogenic (P)" or "affected (A)" by any tool are defined as pred_B.

[0048] We screened 33 patients from a high-hereditary-risk breast cancer cohort. BRCA1 / 2 Further functional validation was performed on variants of unknown significance (see identification process). Figure 6 The remaining specific technical details are the same as in Example 2. The results showed that 33 variants of unknown significance were significantly distinguished (…). Figure 7 Of these, 5 variants (2 of them)BRCA1 : c.4211T>G, c.100C>T; 3 BRCA2 : c.475+3A>G, c.476-3C>A, c.7871A>C) showed low functional scores (<0.5), and the cell pool carrying these variants decreased significantly in abundance over time ( P <0.01), suggesting that they caused significant loss of gene function. The above loss-of-function variants accounted for 9.1% (2 / 22) of all BRCA1 ambiguous variants and 7.3% (3 / 41) of all BRCA2 ambiguous variants. Among the 5 loss-of-function variants detected, 3 were missense variants, 2 were splice-site variants, and no small indel variants were identified as loss-of-function variants. Among all the loss-of-function missense variants identified, at least 5 / 7 computer prediction tools predicted them to be "pathogenic" or "deleterious"; 1 loss-of-function splice-site variant was predicted to be "pathogenic" or "VUS" by 2 / 3 tools, and the other was predicted to be "pathogenic" or "impact function" by 3 / 3 tools (Table 2). BRCA1 c.100C>T is located in the RING domain, BRCA2 c.7871A>C is located in the helical domain, and the remaining 3 loss-of-function variants are not located in specific functional domains. By comparing with multiple large independent functional research data, it was found that the functional classification results of all ambiguous variants with previously reported functional results in this study were highly consistent (100% consistency rate, 22 / 22) Figure 8 , suggesting that the method has good repeatability and supports its potential as a tool for functional assessment of ambiguous variants.

Claims

1. A kind BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, Includes the following steps: S1. For each undetermined variant to be tested, design one gRNA and two HDR templates for single-point editing. One of the two HDR templates contains the undetermined variant sequence, and the other contains the control variant sequence. S2, for each variant of unknown significance or control variant, gRNA, HDR template and Cas9 enzyme are co-transferred into haploid host cells for gene editing; S3, Dynamic Abundance Detection: Detection of the abundance of cells carrying variants of unknown significance after gene editing and culturing. S4, based on the results of dynamic abundance detection, perform functional scoring of variants of unknown significance.

2. As described in claim 1 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, The haploid host cell is the haploid HAP1 cell.

3. As described in claim 2 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, Haploid HAP1 cells will LIG4 Gene knockout.

4. As described in claim 1 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, The control variants were selected from synonymous mutations that were as close as possible to the variants whose significance was unclear.

5. As described in claim 4 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, The control variants were selected from known or potentially benign variants within ±3 bp of the variants whose significance was unclear.

6. As described in claim 1 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, gRNA selection focuses on gRNAs with cleavage sites within 10 nt of variants of unknown significance, high targeting efficiency scores, and low off-target risk.

7. As described in claim 1 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, Introduce 0-3 blocking mutations located near the PAM site or adjacent to the 3' end of the gRNA into the HDR template. All blocking mutations were confirmed to be benign or potentially benign variants. Choose the strand that is not complementary to the gRNA as the HDR template strand; For missense variants, splice site variants, and small fragment insertion or deletion variants <6bp, the HDR template length is designed to be 80-100nt; The two HDR templates used for the same undetermined variant are of the same length and contain the same blocking mutation.

8. As described in claim 1 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, Before functional validation, multiple computer prediction tools are used to filter out variants with low pathogenicity and unclear significance, thus narrowing down the validation targets. Among them, only missense variants, splice site variants, and small fragment insertion or deletion variants with a length ≤6bp that are predicted to be harmful, pathogenic, or affect function by at least one computer prediction tool are included in further functional validation trials.

9. As claimed in claim 1 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, In step S3, after the gene-edited cells are cultured for 3-5 days, a portion of the cells are harvested for the first gene sequencing. The remaining cells are cultured for at least 2 passage cycles and then harvested for the second gene sequencing. The sequence data are statistically analyzed, and the sequences carrying the target variant, the blocking mutation, or only the target variant are counted. This count represents the abundance of cells carrying variants of unknown significance.

10. The claim 9 BRCA1 / 2 A method for functional verification of variants of unknown gene significance, characterized in that, In step S4, the formula for calculating the functional score S of the unsigned variant function score is: S = (A vus, Dy ×A Control, Dx ) / (A vus, Dx ×A Control, Dy ), Among them, A vus, Dx This was the first gene sequencing test to determine the abundance of cells carrying variants of unknown significance. A vus, Dy The purpose of a second gene sequencing assay was to determine the abundance of cells carrying variants of unknown significance. A Control, Dx The first gene sequencing was used to determine the abundance of cells carrying the control variant. A Control, Dy To detect the abundance of cells carrying the control variant in a second gene sequencing assay. Low functional score S reflects undetermined significance of the variation being tested. BRCA1 / 2 Loss of gene function.

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