Partitioned Amplicon Sequencing for Accurate cfDNA Variant Calling
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Solution Overview
Problem
Existing sequencing methods for detecting cancer from cell-free DNA in bodily fluids face challenges due to the low number and diversity of nucleic acids, making it difficult to distinguish genuine genetic variations from amplification and sequencing errors, especially in non-invasive tests.
Innovation Solution
A method involving linking sample indexes to nucleic acid molecules, partitioning them into aliquots, amplifying, sequencing, and grouping reads by sample and partition indexes to determine start and stop points, allowing for accurate alignment and variant calling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If molecular barcodes are used to randomly assort among nucleic acid molecules, then grouping of amplicons according to original molecule is improved, but the complexity of the sequencing process increases
Solution Approach 1:
The patent divides the sequencing process into distinct segments: (a) linking sample indexes to nucleic acid molecules, (b) partitioning pooled molecules into aliquots, (c) amplification, (d) sequencing, (e) alignment to reference sequence, (f) grouping reads by sample index and alignment parameters, and (g) variant calling. This segmentation allows systematic handling of complexity while maintaining accuracy in variant detection from cell-free DNA.
2Productivity
If nucleic acids from multiple samples are pooled together, then productivity is improved, but the difficulty of detecting and measuring genuine variations worsens
Solution Approach 1:
Sample indexes serve as intermediary markers that link nucleic acid molecules to their source samples. These indexes are incorporated during adapter ligation or amplification and persist through sequencing, enabling computational demultiplexing of pooled samples. This intermediary mechanism allows high-throughput pooling while maintaining the ability to detect and attribute genetic variations to specific samples through bioinformatic processing.
Data Source
AI summary
Sequencing methods for sequencing populations of nucleic acid molecules in which sequencing reads of amplicons are grouped into families according to the nucleic acid molecule of origin by partitioning, sample indexes and information from the sequencing reads, such as start and end points. The methods described herein provide many advantages over other sequencing analysis methods, including the identification of sequencing reads deriving from the same nucleic acid in the original sample while minimizing the number of aliquots that are processed.