Non-Invasive Prenatal Genetic Variation Detection via Statistical Window Analysis

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Solution Overview

Problem

Current methods for detecting chromosomal microdeletion/microduplication syndromes in fetuses are invasive, inefficient, and lack a universal screening method, making it difficult to diagnose these conditions prenatally, which can lead to delayed diagnosis and significant health and economic burdens.

Innovation Solution

A high-throughput sequencing method that analyzes DNA from maternal samples to detect copy number variations and aneuploidy with high specificity and accuracy, reducing the need for invasive procedures and improving detection efficiency by using a computer-implemented approach to identify genetic variations through statistical analysis of sequencing data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If invasive molecular diagnostic methods (amniotic fluid sampling, FISH, Array CGH) are used to detect microdeletion/microduplication syndromes, then detection accuracy is improved, but procedural invasiveness and resource consumption increase

Engineering Contradiction:
Improvedetection accuracyVSAvoidprocedural invasiveness
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent uses cell-free fetal DNA in maternal plasma as an intermediary substance to obtain fetal genetic information without direct fetal sampling. This mediator allows non-invasive detection while maintaining diagnostic accuracy for microdeletion/microduplication syndromes

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces invasive mechanical procedures (amniocentesis, chorionic villus sampling) with a non-invasive blood draw from the mother. This substitution eliminates surgical risks while preserving the ability to detect chromosomal abnormalities

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If high-depth sequencing with large data generation (243 million short reads) is performed to detect fetal microdeletion, then detection capability is improved, but resource consumption and time efficiency deteriorate

Engineering Contradiction:
Improvedetection capabilityVSAvoidtime efficiency
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent applies low-depth whole-genome sequencing (0.1x coverage) which provides sufficient statistical power to detect copy number variations through population-level analysis, avoiding the excessive resource consumption of high-depth sequencing while maintaining detection capability

Inventive Principle:
Principle #16Partial or excessive action

Solution Approach 2:

The patent segments the genome into genomic windows and analyzes read depth distribution across these segments. This segmentation allows detection of copy number variations through statistical analysis of aggregated data rather than requiring deep sequencing of individual loci

Inventive Principle:
Principle #1Segmentation

3Ease of operation

If routine clinical methods (chromosome karyotyping) are used for prenatal screening, then ease of operation is maintained, but detection resolution deteriorates due to micro level variations

Engineering Contradiction:
Improveease of operationVSAvoiddetection resolution
Core Design Contradiction:
Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces traditional mechanical karyotyping methods with automated high-throughput sequencing and bioinformatic analysis. This substitution maintains operational simplicity while achieving superior resolution for detecting microdeletions and microduplications

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentEP2772549B8Method for detecting genetic variation
Publication Date: 2019.09.11 BGI GENOMICS CO LTD

AI summary

The present invention relates to a method for detecting genetic variation, comprising the following steps: acquiring reads from a test sample; aligning said reads with a reference genome sequence; dividing said reference genome sequence into windows, calculating the number of said reads which are aligned to each window, and acquiring the statistic for each window on the basis of the number of said reads; and for a fragment of the reference genome sequence, acquiring the genetic variation sites on the basis of the change in the statistics of all the windows thereon in the fragment of the reference genome sequence.