eccDNA Remnant Classification via Sequencing Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for analyzing biological samples fail to identify linear DNA molecules that are remnants of in vivo cleavage of circular DNA molecules, such as eccDNA, which can be crucial for determining properties like cancer classification.
Innovation Solution
The method involves classifying linear DNA molecules in a biological sample using sequence information from random whole genome sequencing, without the need for in vitro enrichment or cleavage of circular DNA, to identify eccDNA remnants and determine their properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in vitro enrichment steps (exonuclease treatment, RCA) are performed to identify eccDNA, then the detection capability for circular DNA is improved, but the device complexity and procedural cost increase
Solution Approach 1:
The patent extracts and analyzes only the relevant portion of DNA data - specifically the end sequences of linear DNA molecules - from whole genome sequencing data. By focusing on the 5' and 3' end sequences and their mapping patterns to the reference genome, the method identifies eccDNA remnants without requiring physical enrichment steps, thus reducing procedural complexity while maintaining detection capability
Solution Approach 2:
The patent uses in silico analysis to create a computational model of eccDNA detection. Instead of physically enriching and manipulating eccDNA molecules through multiple wet-lab steps, the method creates a digital representation by analyzing sequencing data patterns, particularly the characteristic mapping of end sequences that indicate circularization events, thereby eliminating the need for complex physical enrichment procedures
2Ease of operation
If random whole genome sequencing is performed without enrichment steps, then the ease of operation is improved, but the measurement precision for detecting eccDNA is reduced
Solution Approach 1:
The patent changes the analytical parameters used to interpret sequencing data. Instead of requiring physical enrichment to achieve detectable signals, the method changes to analyzing specific parameters of the sequencing data - particularly the mapping coordinates and orientation of end sequences - to identify the characteristic patterns of eccDNA remnants, thereby maintaining detection sensitivity while using simpler procedures
Solution Approach 2:
The patent replaces mechanical/enzymatic enrichment systems with computational analysis. Instead of using exonucleases, rolling circle amplification, or other physical/chemical enrichment methods, the invention substitutes these with in silico analysis of sequencing data, using computational algorithms to identify eccDNA remnants through their characteristic end sequence mapping patterns, thus achieving both ease of operation and measurement precision
3Manufacturing precision
If in vitro cleavage steps are performed on circular DNA, then the manufacturing precision of linearized products is improved, but the loss of time and additional processing steps increase
Solution Approach 1:
The patent performs preliminary identification of eccDNA remnants through computational analysis of end sequence mapping patterns before any physical manipulation. By identifying candidate eccDNA molecules in silico based on the characteristic arrangement of their end sequences in the reference genome, the method eliminates the need for subsequent in vitro cleavage steps, thereby saving time while maintaining the ability to obtain high-quality linearized products when needed
Data Source
AI summary
Methods and systems are described herein that include using sequence reads of linear DNA molecules naturally present in a biological sample to classify a set of the linear DNA molecules that are eccDNA remnants, i.e., linear DNA molecules resulting from in vivo opening of eccDNA molecules. In various embodiments, characteristics of the classified eccDNA remnants can be analyzed to determine a property of the biological sample or of the subject from whom the biological sample was obtained. Examples of properties that can be determined include a classification of a pathology, e.g., a level of a cancer, or an inferred age of the subject.