Overview

There are millions of DNA sequences in a patient’s sample. Rare variant sequences contain vital disease-state information, but current technologies struggle to detect these rare variant sequences.

Our proprietary methodology, blocker displacement amplification (BDA) is a PCR-based rare allele enrichment method that allows for accurate detection and quantitation of SNVs and indels down to 0.01% VAF in a highly multiplexed environment. BDA improves the limit of detection on NGS and PCR platforms.

Efficient Enrichment to Detect More with Less Using BDA

Ultrasensitive

Removes >99% of wildtype DNA sequences for detection of somatic SNVs and indels down to 0.01% VAF

Quantitative

Accurately quantitate mutations down to 0.01% VAF

Cost Effective

Increases efficiency by reducing turnaround time and/or increasing sequencing capacity

Robust Enrichment

 Adaptable to a range of operational conditions

Platform Flexibility

Compatible with NGS and PCR

How BDA Works

 

    • BDA Mechanism

    • BDA selectively blocks the amplification of normal DNA sequences, allowing better detection of rare mutations. By enriching the rare variant sequences 1,000-fold over normal sequences, BDA enables detection of low frequency mutations.

  • Quantitative BDA

  • By using unique molecular identifiers (UMIs) with our BDA technology we can quantitate the true number of sequences present in a sample.

BDA Assays

Ultrasensitive Mutation Detection using qPCR

Low-Depth NGS Sequencing to 0.01% VAF

Publication References:

Single-Tube qPCR Detection and Quantitation of Hotspot Mutations Down to 0.01% Variant Allele Fraction. Analytical Chemistry. (2021).

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Calibration-free NGS quantitation of mutations below 0.01% VAF. Nature Communications. (2021).

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Selective multiplexed enrichment for the detection and quantitation of low-fraction DNA variants via low-depth sequencing. Nature Biomedical Engineering. (2021).

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Multiplexed enrichment of rare DNA variants via sequence-selective and temperature-robust amplification. Nature Biomedical Engineering. (2017).

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