Rare Event Detection Using Error-corrected DNA and RNA Sequencing.

Area of Science:

• Genomics
• Molecular Biology
• Cancer Research

Background:

• Next-generation sequencing (NGS) is crucial for characterizing clonal mutations in malignancy.
• Standard NGS has limitations in detecting rare mutations due to a high error rate (~0.5-2.0%) and a detection limit of >0.02 variant allele fraction (VAF).
• Detecting rare residual disease (<0.0001 VAF) is critical for improving patient outcomes, particularly in leukemia treatment.

Purpose of the Study:

• To develop a novel sequencing method to overcome the limitations of standard NGS for detecting rare mutations.
• To enhance the sensitivity and accuracy of variant allele fraction (VAF) detection in DNA and RNA sequencing.
• To enable the tracking of clonal mutations at significantly lower VAFs than currently possible with NGS.

Main Methods:

• Developed Error-corrected DNA and RNA Sequencing (ECS), a method employing molecular tagging.
• Utilized a 16 bp random index for error correction on individual DNA/RNA molecules.
• Incorporated an 8 bp patient-specific index for multiplexing samples.

Main Results:

• The ECS method achieves detection limits for mutations two orders of magnitude lower than standard NGS.
• Successfully detected clonal mutations at variant allele fractions (VAFs) as low as 0.0001.
• Demonstrated the capability to track rare mutations with unprecedented sensitivity.

Conclusions:

• Error-corrected DNA and RNA Sequencing (ECS) significantly enhances the detection of rare clonal and subclonal mutations.
• ECS offers a substantial improvement over conventional NGS, pushing the limit of detection to 0.0001 VAF.
• This advanced sequencing approach holds promise for improved diagnostics and monitoring of residual disease in cancer patients.