4.7 Article

Single molecule molecular inversion probes for targeted, high-accuracy detection of low-frequency variation

Journal

GENOME RESEARCH
Volume 23, Issue 5, Pages 843-854

Publisher

COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.147686.112

Keywords

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Funding

  1. NHLBI GO Exome Sequencing Project
  2. Lung GO Sequencing Project [HL-102923]
  3. WHI Sequencing Project [HL-102924]
  4. Broad GO Sequencing Project [HL-102925]
  5. Seattle GO Sequencing Project [HL-102926]
  6. Heart GO Sequencing Project [HL-103010]
  7. National Cancer Institute [CA160080]
  8. National Institute on Aging [AG039173]
  9. Achievement Rewards for College Scientists
  10. Department of Laboratory Medicine, University of Washington Medical Center

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The detection and quantification of genetic heterogeneity in populations of cells is fundamentally important to diverse fields, ranging from microbial evolution to human cancer genetics. However, despite the cost and throughput advances associated with massively parallel sequencing, it remains challenging to reliably detect mutations that are present at a low relative abundance in a given DNA sample. Here we describe smMIP, an assay that combines single molecule tagging with multiplex targeted capture to enable practical and highly sensitive detection of low-frequency or subclonal variation. To demonstrate the potential of the method, we simultaneously resequenced 33 clinically informative cancer genes in eight cell line and 45 clinical cancer samples. Single molecule tagging facilitated extremely accurate consensus calling, with an estimated per-base error rate of 8.4 x 10(-6) in cell lines and 2.6 x 10(-5) in clinical specimens. False-positive mutations in the single molecule consensus base-calls exhibited patterns predominantly consistent with DNA damage, including 8-oxo-guanine and spontaneous deamination of cytosine. Based on mixing experiments with cell line samples, sensitivity for mutations above 1% frequency was 83% with no false positives. At clinically informative sites, we identified seven low-frequency point mutations (0.2%-4.7%), including BRAF p.V600E (melanoma, 0.2% alternate allele frequency), KRAS p.G12V (lung, 0.6%), JAK2 p.V617F (melanoma, colon, two lung, 0.3%-1.4%), and NRAS p.Q61R (colon, 4.7%). We anticipate that smMIP will be broadly adoptable as a practical and effective method for accurately detecting low-frequency mutations in both research and clinical settings.

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