CRISPR DNA Break Repair Alignment for Accurate Indel Profiling
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Solution Overview
Problem
Existing methods for identifying and characterizing double-stranded DNA break repair sites lack accuracy due to non-specific targeting by CRISPR enzymes, leading to undesired mutations and variable alignment choices, which result in incorrect indel annotations and lower accuracy.
Innovation Solution
A computer-implemented process using a processor to analyze sample sequence data, align it with an enzyme-specific position-specific scoring matrix, and re-align indels near the canonical cut site, employing a modified Needleman-Wunsch aligner with position-specific gap penalties to improve alignment accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard alignment algorithms (Needleman-Wunsch, bwa) are used to align sequence reads to target sites, then the process is simple and fast, but alignment accuracy decreases when multiple equally valued alignments exist, leading to incorrect indel annotations
Solution Approach 1:
The patent applies local quality by implementing position-specific scoring matrices that assign different weights to matches and mismatches at different positions relative to the CRISPR cut site. This allows the alignment algorithm to prioritize biologically relevant regions (near the cut site) over other regions, improving accuracy without requiring complete redesign of the alignment process.
Solution Approach 2:
The patent performs preliminary actions by first identifying the canonical cut site position, then pre-calculating position-specific scoring parameters before performing the actual alignment. This preparatory step enables the alignment algorithm to use biologically informed weights, resolving equally valued alignments based on their proximity to the cut site rather than requiring post-processing validation.
2Reliability
If CRISPR enzymes are used for targeted DNA editing, then specific genomic positions can be edited, but non-specific targeting occurs resulting in undesired mutations at off-target locations
Solution Approach 1:
The patent implements feedback by using the alignment results to identify both on-target and off-target editing events. By comparing aligned reads against the expected target sequence and analyzing deviations, the system provides feedback about actual editing outcomes, enabling differentiation between desired on-target edits and undesired off-target mutations.
Solution Approach 2:
The patent replaces the mechanical/biological CRISPR enzyme system with a computational alignment system that can precisely distinguish between on-target and off-target sites. Instead of relying solely on enzyme specificity, the computational method substitutes biological recognition with algorithmic sequence comparison, achieving higher precision in identifying true target sites versus off-target sites.
3Measurement precision
If random selection is used among equally valued alignment options, then the process is simple, but variable alignment choices lead to incorrect indel annotations and lower accuracy
Solution Approach 1:
The patent changes parameters by transforming the alignment scoring from uniform weights to position-specific weights based on distance from the cut site. This parameter change resolves equally valued alignments by assigning different scores to alignments with indels at different positions, eliminating the need for random selection while maintaining computational simplicity.
Data Source
AI summary
Described herein is a system and process for identifying and characterizing double-stranded DNA break repair sites that are based on biological information and have improved accuracy. Also described is a sequence alignment process that uses biological data to inform the alignment matrix for position specific alignment scoring, resulting in the identification of noncanonical target sites.