Systems and methods to detect rare mutations and copy number variation

What is this patent about?

’600 is related to the field of genetic analysis and bioinformatics, specifically focusing on the high-sensitivity detection of rare mutations and copy number variations (CNVs) within cell-free DNA (cfDNA). The technology addresses the challenge of identifying minute quantities of tumor-derived or fetal genetic material that co-circulate with a vast majority of healthy germline DNA in bodily fluids like blood plasma.

The underlying idea behind ’600 is to treat the sequencing process as a noisy communication channel and apply a digital-inspired error-correction strategy to recover the original genetic message. By attaching molecular barcodes to individual fragments before amplification, the system can track all progeny molecules back to their single parent strand. This allows the system to distinguish between true biological variants and the inevitable noise introduced by PCR amplification or sequencing errors, effectively collapsing multiple reads into a single, high-fidelity consensus sequence.

The claims of ’600 focus on a specific method for preparing cfDNA libraries by ligating adapters containing a calculated number of molecular barcodes. The number of unique barcodes, *n*, is mathematically constrained based on the expected number of duplicate molecules—those naturally sharing the same start and stop positions—to ensure that biological duplicates can be distinguished from one another. The process involves tagging these parent molecules, performing universal amplification, and then selectively enriching the progeny for specific genomic regions of interest.

In practice, the invention works by first bottlenecking or quantifying the initial genetic material to determine the diversity of the sample. By using a specific ratio of barcodes to the mean number of expected duplicate fragments, the method ensures a high probability that any two identical fragments from different cells receive different tags. After sequencing, the bioinformatics pipeline groups reads into families based on these barcodes and their genomic coordinates, allowing the system to filter out stochastic errors that appear in only a subset of a family’s reads.

This approach differs from prior methods by significantly increasing the conversion efficiency of the library preparation and using digital collapsing to bypass the standard error rates of sequencing platforms. While traditional sequencing might struggle to detect mutations below a 1% frequency due to background noise, this method can reliably identify rare variants at frequencies as low as 0.1%. This sensitivity is achieved by shifting the focus from individual read quality to the collective evidence provided by an entire family of molecules derived from a single original template.