Genetic Analysis Sequencing Subsets for High-GC Variant Capture
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Solution Overview
Problem
Current whole genome and/or exome sequencing methods are costly and fail to capture many biomedically important variants, particularly in regions with high CG content and repetitive elements, leading to inadequate sequencing performance.
Innovation Solution
A method involving the production of multiple subsets of nucleic acid molecules with varying features such as genomic regions, GC content, and molecular size, followed by conducting separate assays on each subset and combining the results using a computer processor to analyze the nucleic acid sample.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard whole genome or exome sequencing methods are used, then sequencing can be performed, but sequencing sensitivity and accuracy deteriorate in regions with high CG content (>70%) and repetitive elements
Solution Approach 1:
The genome is divided into multiple subsets based on different features (genomic regions, GC content, molecular size). Each subset is processed separately with optimized protocols tailored to its specific characteristics, allowing high-accuracy sequencing in challenging regions like high CG content areas and repetitive elements that would fail with standard uniform methods
Solution Approach 2:
Different sequencing protocols and conditions are applied to different genomic subsets according to their specific requirements. For example, subsets with high GC content receive specialized handling different from low GC subsets, ensuring each region achieves optimal sequencing quality rather than using a one-size-fits-all approach
2Productivity
If standard exome enrichment kits are used, then exome sequencing can be performed, but biomedically important non-exomic and exomic regions are not captured
Solution Approach 1:
The sequencing system is designed to handle multiple types of genomic regions (exomic, non-exomic, repetitive elements, high CG content regions) within a single unified platform. By creating multiple subsets with different enrichment strategies and processing them through the same sequencing infrastructure, the system achieves both high throughput and comprehensive variant capture across diverse genomic regions
3Measurement precision
If multiple subsets of nucleic acid molecules are produced and analyzed separately, then sequencing sensitivity and accuracy improve, but device complexity and processing time increase
Solution Approach 1:
Multiple subsets of nucleic acid molecules are pooled together into a single combined library that is then sequenced in one run. This merging approach maintains the sensitivity and accuracy benefits of subset-specific optimization while eliminating the need for multiple separate sequencing runs, thereby reducing device complexity and processing time
Data Source
AI summary
This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.