Cluster Number Estimation via Single-Molecule Imaging
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Solution Overview
Problem
Current next-generation sequencing technologies face challenges in accurately quantifying libraries to predict cluster numbers, leading to issues of underloading or overloading, which affect sequencing data yield and quality.
Innovation Solution
A method involving imaging template hybridization at the single molecule level on a solid support with immobilized capture primers, labeling, and signal detection to estimate cluster numbers before amplification, allowing for adjustments to achieve optimal cluster densities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If library quantification is performed using conventional methods, then the sequencing process can proceed, but accurate prediction of cluster numbers is compromised leading to underloading or overloading
Solution Approach 1:
The patent performs imaging and quantification of template strands at the template hybridisation stage, before cluster amplification occurs. This preliminary measurement allows accurate prediction of cluster numbers and enables correction of loading issues before they affect sequencing data quality
Solution Approach 2:
The patent implements a feedback mechanism where the number of template strands is measured and used to predict cluster numbers, which then informs adjustments to achieve optimal cluster densities. This closed-loop approach ensures accurate cluster number prediction and prevents underloading or overloading
2Productivity
If cluster density is not optimized, then sequencing can proceed without adjustments, but sequencing efficiency is reduced and costs increase
Solution Approach 1:
The patent performs quantification and prediction of cluster numbers before the sequencing run begins, allowing proactive optimization of cluster density. This prevents inefficiencies during sequencing and reduces waste of reagents and resources, thereby improving productivity and reducing costs
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
Enables accurate prediction and correction of cluster numbers, optimizing sequencing efficiency and reducing costs by ensuring proper loading on the flow cell, thereby improving data quality and throughput.
Implementation Method 1
providing template strands able to hybridise to at least some of said capture primers
Implementation Method 2
labelling the template strands or extensions thereof
Implementation Method 3
providing a solid support having a plurality of capture primers immobilised thereon
Data Source
AI summary
The present invention relates to methods of imaging template hybridisation for estimating cluster numbers prior to solid phase amplification and sequencing. More particularly, an initial round of imaging is carried out at the single molecule template hybridisation stage which allows a general estimation of cluster numbers prior to clusters being formed. Amplification of the signal allows single molecule imaging to be carried out using standard sequencing imaging apparatus.