Epigenetic DNA Trait Identification via Methylation-Dependent Digestion
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Solution Overview
Problem
Existing methods for determining the source of biological materials from evidence samples, particularly using epigenetic-based patterns, face challenges with sensitivity in degraded samples, reproducibility, ease of use, and consumption of precious samples, and are not readily adaptable for use with massively parallel sequencing (MPS) workflows.
Innovation Solution
A method involving digestion of DNA samples with a methylation-dependent endonuclease, followed by multiplex PCR amplification, sequencing with MPS, and applying a classification algorithm to identify traits by normalizing sequence counts, which does not require fluorescently-labeled primers and is compatible with MPS-based workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If capillary electrophoresis (CE) is used for epigenetic-based tissue source determination, then sensitivity and specificity are improved, but adaptability to MPS-based workflows deteriorates
Solution Approach 1:
The patent adapts the CE-based epigenetic analysis method to work with MPS platforms by modifying the workflow to include MPS-compatible steps: using unlabeled primers instead of fluorescent labels, incorporating size selection, and integrating with standard MPS library preparation. This allows the same epigenetic markers to be analyzed through both CE and MPS platforms, achieving universality across different sequencing technologies while maintaining the sensitivity and specificity of epigenetic-based tissue source determination.
2Measurement precision
If traditional epigenetic-based methods are used, then tissue source identification capability is improved, but sample consumption increases
Solution Approach 1:
The patent implements a targeted approach by selecting specific epigenetic markers and loci that are most informative for tissue source identification, rather than analyzing the entire genome. The method uses a panel of selected CpG sites and restriction enzyme digestion to focus analysis on key regions, thereby achieving accurate tissue source identification with minimal sample consumption. The workflow includes optional amplification steps that can be adjusted based on sample availability, allowing partial action when samples are limited.
3Productivity
If multiplex PCR amplification is used, then productivity is improved, but manufacturing precision deteriorates due to amplification bias
Solution Approach 1:
The patent incorporates normalization steps that use reference loci and control samples to detect and correct for amplification bias. The workflow includes measuring amplification efficiency across multiple loci and using this information to normalize the data, thereby compensating for variations introduced during multiplex PCR. This feedback mechanism allows the method to maintain high productivity through multiplexing while correcting for the resulting biases in quantification.
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 method enhances sensitivity and specificity for identifying traits such as tissue source, cell type, and disease states, while being compatible with existing MPS protocols, reducing sample consumption and inter-operator variability.
Implementation Method 1
digesting a DNA sample with a methylation-dependent endonuclease
Implementation Method 2
amplifying a plurality of loci of the digested DNA sample using a multiplex polymerase chain reaction (PCR)
Data Source
AI summary
Illustrative embodiments of systems and methods for the identification of traits associated with DNA samples using epigenetic-based patterns detected via massively parallel sequencing (MPS) are disclosed. Illustrative embodiments may involve digesting a DNA sample with a methylation-dependent endonuclease, amplifying loci of the digested DNA sample (including a positive control locus that does not contain a restriction site for the methylation-dependent endonuclease) using a multiplex PCR to produce amplicons, sequencing the amplicons using an MPS instrument to generate sequence reads, determining a sequence count for each of the loci by comparing each of the sequence reads to reference sequences, normalizing the sequence count for each of the loci to the sequence count of the positive control locus, and identifying a trait associated with the DNA sample by applying a classification algorithm to the normalized sequence counts.