Nucleic Acid Normalization via Capture Tags for Sequencing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current sequencing technologies face challenges in accurately processing biological samples with high variability in target sequence abundance, leading to decreased accuracy and overwhelmed detection of low-abundance sequences, particularly in Sanger and next-generation sequencing (NGS) systems.
Innovation Solution
A method involving the use of capture tags and moieties to normalize target sequences by attaching unique identifying features to nucleic acid samples, pooling them, and adding specific capture moieties to cap the amount of targets, thereby minimizing extreme variation and allowing for simultaneous analysis and consolidation of multiple samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sequencing methods are used without normalization, then the sequencing process can be completed, but high-abundance targets overwhelm low-abundance targets leading to decreased accuracy
Solution Approach 1:
The patent applies preliminary action by performing normalization of target sequence abundance before the sequencing step. Capture tags are attached to targets and capture moieties are added to cap the amount of targets in advance, ensuring that high-abundance targets do not overwhelm low-abundance targets during subsequent sequencing, thereby improving measurement precision
Solution Approach 2:
The patent changes the concentration parameter of target sequences through normalization. By attaching capture tags and adding capture moieties to cap target amounts, the method adjusts the abundance parameter of different targets to a comparable range, enabling accurate detection of both high and low-abundance targets without overwhelming the sequencing system
2Productivity
If multiple samples are processed separately, then each sample can be analyzed individually, but the process is time-consuming and inefficient
Solution Approach 1:
The patent merges multiple samples into a single pooled sample for simultaneous processing. Capture tags with unique identifying features are attached to targets from different samples, allowing them to be combined in one tube. Capture moieties are then added to normalize the pooled sample, enabling parallel processing of multiple samples and significantly improving productivity while reducing processing time
Solution Approach 2:
The patent uses capture tags as intermediaries to enable pooling and simultaneous processing of multiple samples. Each capture tag contains a unique identifying feature that allows differentiation of targets from different samples after pooling, serving as a mediator that facilitates high-throughput processing while maintaining sample-specific information
3Quantity of substance
If capture tags and moieties are used for normalization, then target abundance variation is minimized, but the process complexity increases
Solution Approach 1:
The patent applies universality by designing a standardized normalization system that can be applied to any target sequence. Capture tags and capture moieties serve universal functions of attaching to targets, enabling pooling, and normalizing abundance across different samples and target types, simplifying the overall process despite the additional components
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and efficiency of sequencing by ensuring that high-abundance targets do not overwhelm low-abundance ones, improving sequencing quality and reducing errors across multiple samples in both Sanger and NGS systems.
Implementation Method 1
attaching capture tags to substantially all of the targets in a given sample, wherein each capture tag comprises an identifying feature and capture moiety-binding domain
Data Source
AI summary
The present disclosure relates to normalization of biological samples, particularly samples comprising nucleic acids to be sequenced. The normalization protocols described herein may be utilized across multiple samples to cap total stoichiometric input and minimize variations in transcript abundance on a per-sample basis in a multiplexed fashion to dramatically increase the accuracy, capacity and efficiency of nucleic acid sequencing.