mRNA Boundary Analysis for Sequencing Sensitivity
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Solution Overview
Problem
Current mRNA sequencing technologies face challenges in accurately evaluating sensitivity and level of detection due to inconsistencies in sample quality and variability in expression, leading to inaccuracies in identifying biomarkers and assessing the presence of low-abundance mRNA targets.
Innovation Solution
The development of improved methodologies and systems that assess detection sensitivity through evaluation of boundary sequences such as exon-exon, gene fusion, and indel boundaries in RNA sequencing results, enabling better assessment of sample quality and input requirements for reliable mRNA sequencing assays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mRNA sequencing methods are used, then sequencing can be performed, but detection sensitivity and level of detection are inaccurate due to sample quality variability
Solution Approach 1:
The patent introduces boundary sequences (exon-exon junctions, gene fusion boundaries, indel boundaries) as intermediary elements that serve as internal references within the sequencing data itself. These boundary sequences act as mediators to assess sample quality and detection sensitivity, allowing the system to normalize for variability and improve measurement precision without requiring external controls
Solution Approach 2:
The methodology implements feedback by using detected boundary sequences to evaluate and characterize the sequencing data quality. The system feeds back information about boundary sequence detection rates and patterns to adjust confidence levels in mRNA target identification, thereby improving reliability of detection sensitivity measurements
2Measurement precision
If conventional sequencing analysis is used, then mRNA expression can be measured, but low-abundance targets are difficult to detect accurately
Solution Approach 1:
Boundary sequences serve as intermediary markers that amplify the detectability of low-abundance mRNA targets. By counting and analyzing boundary sequence occurrences, the system can infer the presence of low-abundance transcripts with higher confidence, effectively using the boundary sequences as mediators to enhance detection capability
Solution Approach 2:
The patent segments mRNA molecules into identifiable boundary components (exon-exon junctions, fusion boundaries, indel boundaries). This segmentation allows the system to detect and count discrete boundary events, making low-abundance targets more detectable through cumulative boundary sequence analysis rather than relying on complete transcript detection
3Adaptability or versatility
If comprehensive genomic evaluation is performed, then more actionable alterations are identified, but the complexity and cost of sequencing increases
Solution Approach 1:
Boundary sequences serve as intermediary metrics that simplify the evaluation of comprehensive sequencing results. By using boundary sequence detection rates and patterns as intermediate measures of data quality, the system can assess comprehensive genomic evaluations more efficiently, reducing the computational and analytical complexity while maintaining versatility
Solution Approach 2:
The patent changes the parameter of analysis from evaluating complete mRNA transcripts to evaluating boundary sequence characteristics (junction types, frequencies, patterns). This parameter change simplifies the complexity of comprehensive genomic evaluation by focusing on discrete, countable boundary events rather than analyzing entire transcript structures
Data Source
AI summary
Methods, systems, and software are provided for detecting gene fusions in a subject with a cancer condition through mRNA boundary analysis of next generation sequencing of a transcriptome or relevant part thereof. Methods, systems, and software are provided for detecting splice variants in a subject with a cancer condition through mRNA boundary analysis of next generation sequencing of a transcriptome or relevant part thereof. Methods, systems, and software are provided for evaluating the complexity of an RNA-seq sequencing reaction through mRNA boundary analysis. Generally, the methods described herein include obtaining sequences of mRNA molecules for a plurality of genes in a sample of a subject. For each gene, an RNA boundary distribution including relative abundance value for each respective RNA boundary sub-sequence of the gene is determined from the plurality of sequences. These abundance values are evaluated using one or more models to provide the analyses described herein.