Ultrasensitive Detection of Rare Mutations using Next-Generation Targeted Resequencing

Publication Date

October 2011

Journal or Book Title

Nucleic Acids Research


With next-generation DNA sequencing technologies, one can interrogate a specific genomic region of interest at very high depth of coverage and identify less prevalent, rare mutations in heterogeneousclinical samples. However, the mutation detection levels are limited by the error rate of the sequencing technology as well as by theavailability of variant-calling algorithms with high statistical power and low false positive rates. We demonstrate that we can robustly detectmutations at 0.1% fractional representation. This represents accurate detection of one mutant per every 1000 wild-type alleles. To achievethis sensitive level of mutation detection, we integrate a high accuracy indexing strategy and reference replication for estimating sequencing error variance. We employ a statistical model toestimate the error rate at each position of the reference and to quantify the fraction of variant base in the sample. Our method is highly specific (99%) and sensitive (100%) when applied to a known 0.1% sample fraction admixture of two synthetic DNA samples to validate our method. As a clinical application of this method, we analyzed nine clinical samples of H1N1 influenza A and detected anoseltamivir (antiviral therapy) resistance mutation in the H1N1 neuraminidase gene at a sample fraction of 0.18%.