Small RNA Binary Predictor Identification via Sequencing Analysis
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Solution Overview
Problem
The diagnostic potential of microRNAs and other small non-coding RNAs has not been fully realized despite their role in human disease, as existing methods focus on up- or down-regulated RNAs rather than identifying unique sequences present in specific cohorts.
Innovation Solution
A method for identifying small RNA predictors by sequencing data analysis, where sequences unique to an experimental cohort are identified and validated using PCR assays, allowing for the detection of binary predictors in biological samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods focus on up- or down-regulated RNAs, then regulatory changes can be detected, but unique sequences present in specific cohorts cannot be identified
Solution Approach 1:
Instead of focusing on regulated RNAs as done conventionally, the patent inverts the approach by focusing on identifying unique sRNA sequences that are present in one cohort but absent in another. This inversion enables discovery of binary predictors with high diagnostic value rather than relying on expression level changes.
Solution Approach 2:
The patent changes the detection parameter from expression level (up/down-regulation) to presence/absence of unique sequences. By quantifying reads for each unique sRNA sequence and comparing cohorts, the method identifies sequences that are binary predictors, fundamentally changing how diagnostic markers are discovered.
2Measurement precision
If sRNA sequencing data is analyzed without trimming adaptors, then sequencing efficiency is maintained, but accurate identification of sRNA sequences at 3' and 5' ends cannot be achieved
Solution Approach 1:
The patent applies preliminary action by trimming user-defined sequencing adaptors from sequence reads before analysis. This preprocessing step enables accurate identification of templated and non-templated variations at the 3' and 5' ends of sRNA molecules, which is essential for precise sequence characterization.
3Reliability
If small RNA predictors are identified using cohort comparison, then diagnostic specificity is improved, but sample size requirements increase
Solution Approach 1:
The patent extracts and focuses only on unique sRNA sequences that differentiate cohorts, discarding sequences common to both. By quantifying reads for each unique sequence and identifying binary predictors, the method achieves high diagnostic specificity while requiring manageable sample sizes (at least 10 per cohort).
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 unlocks the diagnostic utility of miRNAs and other sRNAs by identifying specific sequences predictive of conditions like neurodegenerative diseases, cardiovascular diseases, and cancers, enabling early diagnosis and differentiation among similar diseases.
Implementation Method 1
detecting the presence and absence of selected positive sRNA predictors in RNA extracted from independent experimental and comparator samples using a quantitative or qualitative PCR assay
Data Source
Figure 1A~1B
Figure 2
Figure 3A~3B
AI summary
The invention provides a method for identifying or detecting small RNA (sRNA) predictors of a disease or a condition. The method comprises identifying one or more sRNA sequences that are present in one or more samples of an experimental cohort, and which are not present across a comparator cohort; and optionally identifying one or more sRNA sequences that are present in one or more samples of a comparator cohort, and which are not present across an experimental cohort. In contrast to identifying dysregulated non-coding RNAs (such as miRs that are up- or down-regulated), the invention identifies sRNAs that are binary predictors, that is, present in one cohort (e.g., an experimental cohort) and not another (e.g., a comparator cohort). Further, by quantifying reads for individual sequences (e.g., iso-miRs), without consolidating reads to annotated reference sequences, the invention unlocks the diagnostic utility of miRs and other sRNAs.