Single Cell Tri-Channel Processing for Structural Variation Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting structural variations (SVs) in genomes, particularly somatic structural variations, face challenges in identifying translocations, inversions, and complex SV classes due to high coverage requirements and the presence of repetitive regions, leading to incomplete detection and artefacts from whole genome amplification.
Innovation Solution
The method integrates three layers of information - sequencing read depth, strand orientation, and haplotype phase - using single cell tri-channel processing (scTRIP) to analyze sequencing data, enabling the detection of deletions, duplications, inversions, translocations, and copy-number neutral losses in heterozygosity without requiring breakpoint-spanning reads, thus overcoming limitations of existing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current SV detection methods are used, then deletions and duplications can be detected, but translocations, inversions, and complex SV classes escape detection due to high coverage requirements and repetitive regions
Solution Approach 1:
The patent transitions from one-dimensional read depth analysis to three-dimensional analysis by integrating read depth, strand orientation, and haplotype phase information. This multi-dimensional approach enables detection of translocations, inversions, and complex SVs that are invisible to traditional methods, resolving the contradiction between detection completeness and sequencing complexity
Solution Approach 2:
The patent creates a composite detection framework that combines three distinct types of sequencing information (read depth, strand orientation, haplotype phase) into a unified analysis system. This composite approach leverages the complementary strengths of each information type to detect diverse SV classes without requiring extremely high sequencing coverage
2Quantity of substance
If whole genome amplification is performed to increase DNA amount, then single cell analysis becomes possible, but artefacts are introduced that mimic SVs
Solution Approach 1:
The patent uses strand orientation information as an intermediary to distinguish true SVs from WGA artefacts. By analyzing the directional information of sequencing reads, the method can identify patterns characteristic of genuine structural variations while filtering out artefactual signals introduced during whole genome amplification
Solution Approach 2:
The integrated three-layer analysis system performs self-validation by cross-checking SV candidates across multiple information dimensions. True SVs consistently manifest across read depth, strand orientation, and haplotype phase analyses, while WGA artefacts fail to show consistent patterns, enabling automatic differentiation without external validation
3Measurement precision
If high sequencing coverage is used to detect all SV classes, then detection sensitivity improves, but cost and complexity increase significantly
Solution Approach 1:
The patent applies partial action by focusing sequencing coverage on informative regions and using the three-layer analysis to maximize information extraction from moderate coverage data. The integrated approach of read depth, strand orientation, and haplotype phase allows robust SV detection at lower coverage levels, reducing costs while maintaining sensitivity for all SV classes
Data Source
AI summary
The present invention provides a method for detecting structural variations (SV) within genomes of single cells or population of single cells by integrating a three-layered information of sequencing read depth, read strand orientation and haplotype phase. The method of the invention can detect deletions, duplications, polyploidies, translocations, inversions, and copy number neutral loss of heterozygosity (CNN-LOH), and more. The method of the invention can fully karyotype a genome comprehensively, and may be applied in research and clinical approaches. For example, the methods of the invention are useful for analysing cellular samples of patients for diagnosing or aiding a diagnosis, in reproductive medicine to detect embryonic abnormalities, or during therapeutic approaches based on cellular therapies to quality control genetically engineered cells, such as in adoptive T cell therapy and others. The method of the invention may further be applied in research to decipher the karyotypes of cellular models (cell lines), patient samples, or to further unravel genetic and mechanistic pathways leading to the generation of any SV within genomes.