In:
Clinical Chemistry, Oxford University Press (OUP), Vol. 63, No. 2 ( 2017-02-01), p. 503-512
Abstract:
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 ( & gt;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.
Type of Medium:
Online Resource
ISSN:
0009-9147
,
1530-8561
DOI:
10.1373/clinchem.2016.263897
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2017
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