Low-Coverage Genome-Wide cfDNA Sequencing for Minority Variant Detection
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Solution Overview
Problem
Existing methods struggle to accurately detect and quantify low-frequency minority components in cell-free DNA (cfDNA) from biological samples, particularly in scenarios with high background noise from native cell populations, limiting early diagnosis of transplant rejection, cancer progression, and other conditions.
Innovation Solution
A low-coverage, genome-wide sequencing approach is employed to enrich and analyze cfDNA, using methods such as low-coverage whole genome sequencing (lcWGS), base quality score recalibration, and variant calling to identify minority components, followed by averaging low-confidence estimates across genomic loci for quantitative detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-coverage sequencing is used to detect minority components, then detection precision improves, but sequencing cost and complexity increase significantly
Solution Approach 1:
The patent applies partial action by performing sequencing at low coverage (0.1x to 5x) rather than high coverage, which is sufficient for detecting minority components when combined with multiple other analytical steps. This reduces sequencing cost and complexity while maintaining detection precision through compensatory measures like increased number of loci analyzed and multiple bioinformatics processing steps.
Solution Approach 2:
The patent segments the detection process into multiple independent steps: cfDNA enrichment, low-coverage sequencing, duplicate read marking, base quality recalibration, local realignment, and variant calling. This segmentation allows each step to be optimized independently and reduces the complexity burden on any single step, particularly enabling the use of low-coverage sequencing.
2Ease of manufacture
If low-coverage sequencing is used to reduce cost, then sequencing cost decreases, but detection precision of minority components deteriorates
Solution Approach 1:
The patent merges multiple bioinformatics processing steps (duplicate read marking, base quality score recalibration, local realignment, and variant calling) into an integrated analytical pipeline. This combination compensates for the low sequencing coverage by systematically improving the quality and reliability of variant detection, thereby maintaining detection precision while using cost-effective low-coverage sequencing.
Solution Approach 2:
The patent changes key parameters of the sequencing and analysis process: using low coverage (0.1x-5x), analyzing a large number of genomic loci (5,000 to 10,000,000), and adjusting bioinformatics parameters for duplicate marking and base quality recalibration. These parameter changes collectively enable cost-effective sequencing while maintaining or improving detection precision for minority components.
3Measurement precision
If more genomic loci are analyzed to improve detection accuracy, then detection precision improves, but sequencing time and computational resources increase
Solution Approach 1:
The patent analyzes a large number of genomic loci (5,000 to 10,000,000) at low coverage rather than fewer loci at high coverage. This approach distributes the sequencing effort across many loci, reducing the time and computational resources required per locus while collectively achieving high detection accuracy through the aggregation of data from numerous loci.
Data Source
AI summary
In some aspects, the present disclosure provides a method for analyzing cell free DNA (cfDNA). The method can comprise obtaining a biological sample derived from a subject, wherein the biological sample comprises cfDNA. The method can comprise enriching a proportion of cfDNA within the biological sample. The method can comprise sequencing the cfDNA enriched biological sample using low-coverage, genome-wide nucleic acid sequencing. The method can comprise identifying a plurality of minority components present in the sequenced cfDNA enriched biological sample. The method can comprise assigning a designation that represents a low-confidence estimate of minor variant frequency to individual identified minority components present in the sequenced cfDNA enriched biological sample. The method can comprise averaging a plurality of low-confidence estimates of minor variant frequency across a plurality of sequenced genomic loci to produce an estimation of minority component frequency in the cfDNA enriched biological sample.