Nucleic Acid Fragment Origin Detection via HSNRF Capture
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Solution Overview
Problem
The concentration of cell-free fetal DNA in maternal plasma is low and variable, making it challenging to achieve sufficient accuracy for non-invasive prenatal testing, especially when the proportion is below 4%, and existing methods struggle to accurately distinguish between maternal and fetal DNA or tumor and non-tumor DNA in complex mixtures.
Innovation Solution
A method utilizing long synthetic Target Capture Sequences (TACS) probes and bioinformatics to identify non-random fragmentation patterns, specifically detecting genomic regions with high frequency of non-random fragmentation (HSNRF) to differentiate between tissue types in mixed nucleic acid samples, enabling accurate categorization of nucleic acid fragments as fetal, maternal, tumor, or non-tumor in origin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If nucleic acid sequences from multiple sources are pooled together for analysis, then the diversity of genetic material is improved, but the ability to determine the origin of individual sequences is lost
Solution Approach 1:
The patent applies preliminary action by attaching unique molecular identifiers (UMIs) to nucleic acid sequences at the source before pooling. This pre-marking allows tracking of individual sequences through subsequent mixing and processing steps, enabling origin determination even after diverse samples are combined in a single pool for sequencing analysis.
Solution Approach 2:
The patent uses UMIs as intermediary markers that bridge the gap between diverse sample sources and the final pooled analysis. These unique identifiers act as mediators that carry origin information through the pooling process, allowing computational methods to later trace sequences back to their source samples without requiring physical separation of the mixed nucleic acids.
2Productivity
If computational methods are used to analyze pooled sequencing data, then the processing efficiency is improved, but the accuracy of origin determination decreases
Solution Approach 1:
The patent applies segmentation by dividing the analysis into distinct computational stages: first identifying UMIs in the pooled data, then grouping sequences by their UMI origins, and finally analyzing each origin group separately. This segmented approach maintains processing efficiency while improving accuracy by preventing contamination between different source samples during computational analysis.
Solution Approach 2:
The patent implements feedback through iterative computational refinement where initial origin assignments are validated and refined based on UMI consistency checks. The system uses feedback from the unique identifier patterns to correct potential misassignments and improve the overall accuracy of origin determination while maintaining efficient processing of large pooled datasets.
Data Source
Figure 1(A)~1(B)
Figure 2
AI summary
The present invention relates to a method for determining the origin of a nucleic acid fragment, or detecting a nucleic acid fragment, in a mixture of nucleic acid fragments, comprising the steps of: a) providing a mixture of fragmented nucleic acids stemming from a eukaryotic organism, b) preparing a sequencing library from the mixture of fragmented nucleic acids, c) hybridizing one or more probes to at least one location in said library wherein the mixture of fragmented nucleic acids comprises a hot spot for non-random fragmentation (HSNRF) and said probe covers said HSNRF, d) isolating one or more fragmented nucleic acids from the mixture that are bound by the one or more probes, e) amplifying and sequencing the enriched library, f) determining the size of a fragmented nucleic acid and/or, g) determining the start and/or stop position of the fragmented nucleic acid, and h) identifying the origin of the nucleic acid fragment by utilizing the information from steps (f) and/or (g), thereby determining the origin of/ detecting the nucleic acid fragment.