Genome sequencing as a generic diagnostic strategy for rare disease.

BACKGROUND: To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease. METHODS: We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected. RESULTS: Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected. CONCLUSIONS: GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.

BRCA Testing by Single-Molecule Molecular Inversion Probes.

BACKGROUND: Despite advances in next generation DNA sequencing (NGS), NGS-based single gene tests for diagnostic purposes require improvements in terms of completeness, quality, speed, and cost. Single-molecule molecular inversion probes (smMIPs) are a technology with unrealized potential in the area of clinical genetic testing. In this proof-of-concept study, we selected 2 frequently requested gene tests, those for the breast cancer genes BRCA1 and BRCA2, and developed an automated work flow based on smMIPs. METHODS: The BRCA1 and BRCA2 smMIPs were validated using 166 human genomic DNA samples with known variant status. A generic automated work flow was built to perform smMIP-based enrichment and sequencing for BRCA1, BRCA2, and the checkpoint kinase 2 (CHEK2) c.1100del variant. RESULTS: Pathogenic and benign variants were analyzed in a subset of 152 previously BRCA-genotyped samples, yielding an analytical sensitivity and specificity of 100%. Following automation, blind analysis of 65 in-house samples and 267 Norwegian samples correctly identified all true-positive variants (>3000), with no false positives. Consequent to process optimization, turnaround times were reduced by 60% to currently 10-15 days. Copy number variants were detected with an analytical sensitivity of 100% and an analytical specificity of 88%. CONCLUSIONS: smMIP-based genetic testing enables automated and reliable analysis of the coding sequences of BRCA1 and BRCA2. The use of single-molecule tags, double-tiled targeted enrichment, and capturing and sequencing in duplo, in combination with automated library preparation and data analysis, results in a robust process and reduces routine turnaround times. Furthermore, smMIP-based copy number variation analysis could make independent copy number variation tools like multiplex ligation-dependent probes amplification dispensable.

Translating sanger-based routine DNA diagnostics into generic massive parallel ion semiconductor sequencing.

BACKGROUND: Dideoxy-based chain termination sequencing developed by Sanger is the gold standard sequencing approach and allows clinical diagnostics of disorders with relatively low genetic heterogeneity. Recently, new next generation sequencing (NGS) technologies have found their way into diagnostic laboratories, enabling the sequencing of large targeted gene panels or exomes. The development of benchtop NGS instruments now allows the analysis of single genes or small gene panels, making these platforms increasingly competitive with Sanger sequencing. METHODS: We developed a generic automated ion semiconductor sequencing work flow that can be used in a clinical setting and can serve as a substitute for Sanger sequencing. Standard amplicon-based enrichment remained identical to PCR for Sanger sequencing. A novel postenrichment pooling strategy was developed, limiting the number of library preparations and reducing sequencing costs up to 70% compared to Sanger sequencing. RESULTS: A total of 1224 known pathogenic variants were analyzed, yielding an analytical sensitivity of 99.92% and specificity of 99.99%. In a second experiment, a total of 100 patient-derived DNA samples were analyzed using a blind analysis. The results showed an analytical sensitivity of 99.60% and specificity of 99.98%, comparable to Sanger sequencing. CONCLUSIONS: Ion semiconductor sequencing can be a first choice mutation scanning technique, independent of the genes analyzed.

Interlaboratory diagnostic validation of conformation-sensitive capillary electrophoresis for mutation scanning.

BACKGROUND: Indirect alternatives to sequencing as a method for mutation scanning are of interest to diagnostic laboratories because they have the potential for considerable savings in both time and costs. Ideally, such methods should be simple, rapid, and highly sensitive, and they should be validated formally to a very high standard. Currently, most reported methods lack one or more of these characteristics. We describe the optimization and validation of conformation-sensitive capillary electrophoresis (CSCE) for diagnostic mutation scanning. METHODS: We initially optimized the performance of CSCE with a systematic panel of plasmid-based controls. We then compared manual analysis by visual inspection with automated analysis by BioNumerics software (Applied Maths) in a blinded interlaboratory validation with 402 BRCA1 (breast cancer 1, early onset) and BRCA2 (breast cancer 1, early onset) variants previously characterized by Sanger sequencing. RESULTS: With automated analysis, we demonstrated a sensitivity of >99% (95% CI), which is indistinguishable from the sensitivity for conventional sequencing by capillary electrophoresis. The 95% CI for specificity was 90%-93%; thus, CSCE greatly reduces the number of fragments that need to be sequenced to fully characterize variants. By manual analysis, the 95% CIs for sensitivity and specificity were 98.3%-99.4% and 93.1%-95.5%, respectively. CONCLUSIONS: CSCE is amenable to a high degree of automation, and analyses can be multiplexed to increase both capacity and throughput. We conclude that once it is optimized, CSCE combined with analysis with BioNumerics software is a highly sensitive and cost-effective mutation-scanning technique suitable for routine genetic diagnostic analysis of heterozygous nucleotide substitutions, small insertions, and deletions.

Design and validation of a conformation sensitive capillary electrophoresis-based mutation scanning system and automated data analysis of the more than 15 kbp-spanning coding sequence of the SACS gene.

In this study, we developed and analytically validated a fully automated, robust confirmation sensitive capillary electrophoresis (CSCE) method to perform mutation scanning of the large SACS gene. This method facilitates a rapid and cost-effective molecular diagnosis of autosomal recessive spastic ataxia of Charlevoix-Saguenay. Critical issues addressed during the development of the CSCE system included the position of a DNA variant relative to the primers and the CG-content of the amplicons. The validation was performed in two phases; a retrospective analysis of 32 samples containing 41 different known DNA variants and a prospective analysis of 20 samples of patients clinically suspected of having autosomal recessive spastic ataxia of Charlevoix-Saguenay. These 20 samples appeared to contain 73 DNA variants. In total, in 32 out of the 45 amplicons, a DNA variant was present, which allowed verification of the detection capacity during the validation process. After optimization of the original design, the overall analytical sensitivity of CSCE for the SACS gene was 100%, and the analytical specificity of CSCE was 99.8%. In conclusion, CSCE is a robust technique with a high analytical sensitivity and specificity, and it can readily be used for mutation scanning of the large SACS gene. Furthermore this technique is less time-consuming and less expensive, as compared with standard automated sequencing.