Viral Nucleic Acid DAG Analysis for Quasispecies Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods struggle to accurately identify and characterize viral quasispecies due to rapid genetic mutation and high variability, making it difficult to differentiate between viral and host nucleic acids and effectively represent genetic diversity.
Innovation Solution
Utilizing a directed acyclic graph (DAG) to represent viral genetic diversity, allowing for rapid and efficient alignment and segregation of viral nucleic acid sequences from host sequences, and enabling the identification of viral species or strains by transforming sequence reads into a DAG that represents genetic diversity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional linear sequence alignment methods are used to identify viral sequences, then the process is simple and straightforward, but the methods fail to accurately represent genetic diversity and quasispecies variation
Solution Approach 1:
The patent transforms the traditional linear sequence representation into a two-dimensional directed acyclic graph (DAG) structure. This dimensional change allows the system to represent multiple viral sequences and their variations simultaneously, capturing genetic diversity and quasispecies information that linear methods cannot represent. The DAG nodes represent sequence positions while edges represent possible variations, enabling accurate measurement of viral genetic diversity.
2Productivity
If multiple viral sequences are stored separately in a database, then each sequence is easily accessible, but data redundancy increases and query efficiency decreases
Solution Approach 1:
The patent merges multiple viral sequences into a single integrated DAG structure. Shared sequence regions are represented by common nodes, while variations are represented by divergent edges. This merging eliminates data redundancy by storing common regions once and only storing variations separately, significantly reducing the total data quantity while maintaining fast query performance through the graph's efficient traversal properties.
Solution Approach 2:
Instead of copying entire sequences multiple times, the DAG structure creates a single copy of shared sequence regions and uses references (edges) to point to variations. This virtual copying through graph edges allows multiple sequences to be represented without physically duplicating data, reducing storage requirements while maintaining quick access to all sequence variants.
3Loss of information
If viral sequences are collapsed into a single linear consensus sequence, then the output is simple and easy to interpret, but genetic diversity and rare variants are lost
Solution Approach 1:
The DAG structure provides a dynamic representation that can adapt to show different levels of genetic diversity. The graph can be traversed and visualized in multiple ways - from a simplified consensus view to a detailed view showing all variants and their frequencies. This dynamic flexibility allows the system to preserve complete genetic information while providing interpretation interfaces at different complexity levels, making it both information-rich and user-friendly.
4Productivity
If traditional sequence alignment is used against large reference databases, then comprehensive viral coverage is achieved, but the computational time and resources required are excessive
Solution Approach 1:
The patent merges multiple reference viral sequences into a single compressed DAG structure that maintains comprehensive viral database coverage. By combining shared regions into common nodes and representing variations through edges, the system reduces the total data size that needs to be searched while preserving all viral sequence information. This enables fast alignment operations without sacrificing database completeness.
Data Source
AI summary
The invention provides systems and methods for analyzing viruses by representing viral genetic diversity with a directed acyclic graph (DAG), which allows genetic sequencing technology to detect rare variations and represent otherwise difficult-to-document diversity within a sample. Additionally, a host-specific sequence DAG can be used to effectively segregate viral nucleic acid sequence reads from host sequence reads when a sample from a host is subject to sequencing. Known viral genomes can be represented using a viral reference DAG and the viral sequence reads from the sample can be compared to viral DAG to identify viral species or strains from which the reads were derived. Where the viral sequence reads indicate great genetic diversity in the virus that was infecting the host, those reads can be assembled into a DAG that itself properly represents that diversity.