Accurate detection of low-level mosaic mutations in pediatric acute lymphoblastic leukemia using single molecule tagging and deep-sequencing

Pathogenic mutations in relapse-associated genes in pediatric acute lymphoblastic leukemia may improve risk stratification when detected at subclonal levels at primary diagnosis. However, to detect subclonal mutations upfront, a deep-sequencing approach with high specificity and sensitivity is required. Here, we performed a proof-of-principle study to detect low-level mosaic RAS pathway mutations by deep sequencing using random tagging-based single molecule Molecular Inversion Probes (smMIPs). The smMIP-based approach could sensitively detect variants with allele frequency as low as 0.4%, which could all be confirmed by other techniques. In comparison, with standard deep-sequencing techniques we reached a detection threshold of only 2.5%, which hampered detection of seven low-level mosaic mutations representing 24% of all detected mutations. We conclude that smMIP-based deep-sequencing outperforms standard deep-sequencing techniques by showing lower background noise and high specificity, and is the preferred technology for detecting mutations upfront, particularly in genes in which mutations show limited clustering in hotspots.