Clustered Single-Cell DNA Forensics for Mixture Interpretation

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Solution Overview

Problem

Forensic DNA mixture interpretation in the presence of multiple contributors is prone to inconsistent results due to high levels of allele non-detection and artifacts like stutter, especially in single-cell samples, where traditional methods fail to accurately determine the number of contributors and weight of evidence.

Innovation Solution

The development of a method for clustered single-cell DNA forensics that involves isolating and analyzing individual cells, amplifying biomolecular markers, and using quantitative signal profiles to cluster cells based on similarity, allowing for the determination of the number of contributors and accurate match-statistics through likelihood ratio calculations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional forensic DNA methods are used to analyze mixed samples, then the analysis process is simple, but the results are inconsistent and unreliable in the presence of multiple contributors

Engineering Contradiction:

Improvereliability of DNA mixture interpretationVSAvoidcomplexity of analysis method

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the mixed DNA sample into individual single-cell profiles by isolating and analyzing cells separately. This segmentation allows each cell's genetic profile to be determined independently, avoiding the interpretive challenges of mixture analysis while maintaining reliability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces single-cell isolation and whole-genome amplification as intermediary steps between sample collection and DNA profiling. These intermediaries transform the complex mixture problem into manageable single-cell analyses, improving reliability without requiring direct mixture interpretation.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If single-cell analysis is performed to improve precision, then allele dropout and stutter artifacts increase, but traditional methods fail to accurately determine contributor profiles

Engineering Contradiction:

Improveprecision of contributor profile determinationVSAvoidallele dropout and stutter artifacts

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent merges multiple single-cell profiles into a composite contributor profile by identifying consistent genetic markers across cells. This combining approach overcomes allele dropout in individual cells by using data from multiple cells to reconstruct complete contributor profiles.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent uses iterative analysis where initial profile determinations inform subsequent analysis of other cells. By comparing results across multiple cells and using feedback from consistent patterns, the system distinguishes true genetic signals from stutter artifacts and compensates for allele dropout.

Inventive Principle:

Principle #23Feedback

3Ease of manufacture

If qualitative data only is used to infer number of contributors, then the method is simple to implement, but quantitative information like peak heights is not utilized

Engineering Contradiction:

Improveease of implementationVSAvoidloss of quantitative data

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The patent changes the data parameters from purely qualitative (presence/absence of alleles) to include quantitative measurements (peak heights, signal intensities). By incorporating these additional parameters, the method determines both the number of contributors and their proportional representation, preventing information loss while maintaining implementation feasibility.

Inventive Principle:

Principle #35Parameter changes

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 enables precise determination of contributor profiles in complex DNA mixtures, improving the accuracy and reliability of forensic DNA analysis by accounting for allele dropout and stutter, and providing reliable match-statistics for forensic samples.

Implementation Method 1

amplifying biomolecular markers

Methodology Applied

Scientific EffectPCR amplification:

Implementation Method 2

separating the biomolecular markers (e.g., STR amplicons) using separation techniques (e.g., capillary electrophoresis) that produce a signal

Methodology Applied

Scientific EffectElectrophoresis: Electrophoresis

Data Source

PatentUS20230162044A1Systems and methods for automated analyses of a target genetic profile across genetic profiles in a biological sample

Publication Date: 2023.05.25 NAT UNIV OF IRELAND MAYNOOTH MAYNOOTH UNIV

AI summary

Systems and methods of the present disclosure enable automated analyses of a biological sample by receiving signal profiles of each allele of a set of cells in the sample. Cell vectors are generated by concatenating allele vectors derived from the signal profiles of each cell. A cluster model is utilized to generate clusters of the signal profiles based on the cell vectors to represent contributors. A first probability of observing the cluster given a target contributor donated their DNA and a second probability of observing the cluster given a random contributor donated are determined by comparing the target signal profile to each cluster. A likelihood ratio is determined from a ratio of the first and second probabilities, and the likelihood ratio is averaged across all clustered to output a probability of the target contributor having contributed to the sample.