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.
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.
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Authors: Peer Arts; Jori van der Raadt; Sebastianus H C van Gestel; Marloes Steehouwer; Jay Shendure; Alexander Hoischen; Cornelis A Albers Journal: Nat Commun Date: 2017-05-05 Impact factor: 14.919
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Authors: Robbert D A Weren; Arjen R Mensenkamp; Michiel Simons; Astrid Eijkelenboom; Aisha S Sie; Hicham Ouchene; Monique van Asseldonk; Encarna B Gomez-Garcia; Marinus J Blok; Joanne A de Hullu; Marcel R Nelen; Alexander Hoischen; Johan Bulten; Bastiaan B J Tops; Nicoline Hoogerbrugge; Marjolijn J L Ligtenberg Journal: Hum Mutat Date: 2016-11-09 Impact factor: 4.878
Authors: Gillian Ellison; Miika Ahdesmäki; Sally Luke; Paul M Waring; Andrew Wallace; Ronnie Wright; Benno Röthlisberger; Katja Ludin; Sabine Merkelbach-Bruse; Carina Heydt; Marjolijn J L Ligtenberg; Arjen R Mensenkamp; David Gonzalez de Castro; Thomas Jones; Ana Vivancos; Olga Kondrashova; Patrick Pauwels; Christine Weyn; Eric Hahnen; Jan Hauke; Richie Soong; Zhongwu Lai; Brian Dougherty; T Hedley Carr; Justin Johnson; John Mills; J Carl Barrett Journal: Hum Mutat Date: 2017-12-28 Impact factor: 4.878